How to deploy a Shiny app for production

In February, one hundred fifty-nine new packages made it to CRAN. Here are my Top 40 picks in fifteen categories: Artificial Intelligence, Computational Methods, Ecology, Genomics, Health Sciences, Mathematics, Machine Learning, Medicine, Music,...

This article aims to explain the main data structures in R and how to use them.

The ellmer package for using LLMs with R is a game changer for scientists Why is ellmer a game changer for scientists? In this tutorial we’ll look at how we can access LLM agents through API calls. We’ll use this skill for created structued data fro...

This article shows how to implement CatBoost in R.

This article will discuss simple ways to deploy and manage R models.

I’m very happy to introduce 7 additions to the Big Book of R collection which now stands at almost 450 free, open-source R programming books. A special thanks to Gary and Lucca Scrucca for their submissions. In case you missed it, the Big Book of R bot is live on … The post 7 New Books added to Big Book of R [7/12/2024] appeared first on Oscar Baruffa.

Introduction R programming has become an essential tool in the world of data analysis, offering powerful capabilities for manipulating and analyzing complex datasets. One of the fundamental skills that beginner R programmers need to master is t...

A couple of days ago, in our lab session, we discussed random forrests, and, since it was based on the example in ISLR, we had a quick discussion about the random choice of features, and the “” rule Interestingly, on that one, we can play a bit, and try all choices, and do it again, on a different train/test split, library(randomForest) library(ISLR2) set.seed(123) sim = function(t){ train = sample(nrow(Boston), size = nrow(Boston)*.7) subsim = function(i){ rf.boston

Hey guys, welcome back to my R-tips newsletter. Supply chain management is essential in making sure that your company’s business runs smoothly. One of the key elements is managing inventory efficiently. Today, I’m going to show you how to estimate inve...

Pic by author - using DALL-E 3 When running experiments don’t forget to bring your survival kit I’ve already made the case in several blog posts (part 1, part 2, part 3) that using survival analysis can improve churn prediction. In this blog post I’ll ...

So, you’ve mastered the basics of ggplot2 animation and are now looking for a real-world challenge? You’re in the right place. After reading this one, you’ll know how to download and visualize stock data change through something known as race charts. You can think of race charts as dynamic visualizations (typically bar charts) that display […] The post appeared first on appsilon.com/blog/.

Something a llttle different: Hexbin maps by Jerry Tuttle I recently became acquainted with hexbin maps, so I thought I would experiment with one. In a hexbin map, each geographical region is represented by an equall...

Box plots are a very common tool in data visualization to show how your data is distributed. But they have a crucial flaw. Let’s find out what that flaw is. And if you’re interested in the video version of this blog post, you can find it here: ...

Introduction Data normalization is a crucial preprocessing step in data analysis and machine learning workflows. It helps in standardizing the scale of numeric features, ensuring fair treatment to all variables regardless of their magnitude. In ...

For me, mathematics cultivates a perpetual state of wonder about the nature of mind, the limits of thoughts, and our place in this vast cosmos (Clifford A. Pickover - The Math Book: From Pythagoras to the 57th Dimension, 250 Milestones in the History of Mathematics) I am a big fan of Clifford Pickover and I

Click here to get stared with machine learning in R using caret.

In this article we will review application of clustering to customer order data in three parts.  First, we will define the approach to developing the cluster model including derived predictors and dummy variables; second we will extend beyond a typical “churn” model by using the model in a cumulative fashion to predict customer re-ordering in… Read More »Extending churn analysis to revenue forecasting using R

Machine learning is the study and application of algorithms that learn from and make predictions on data. From search results to self-driving cars, it has manifested itself in all areas of our lives and is one of the most exciting and fast-growing fields of research in the world of data science. The caret package, maintained by Max Kuhn, is the go-to package in the R community for predictive modeling and supervised learning. This widely used package provides a consistent interface to all of R's most powerful machine learning facilities. Need some more convincing? In this post, we explore 3 reasons why you should learn the caret package. Afterward, you can take DataCamp's Machine Learning Toolbox course taught by Zachary Deane-Mayer & Max Kuhn, co-authors of the caret package! 1. It can help you get a data science job Ever read through data science job postings and see words like "predictive modeling", "classification", "regression," or "machine learning"? Chances are if you are seeking a data science position, you will be expected to have experience and knowledge about all of these topics. Luckily, the caret package has you covered. The caret package is known as the "Swiss Army Knife" for machine learning with R; capable of performing many tasks with an intuitive, consistent format. Check out these recent data scientist job postings from Kaggle which are all seeking candidates with knowledge of R and machine learning: Data Scientist Analytics at Booking.com Data Scientist at Amazon.com Data Scientist at CVS Health 2. It's one of the most popular R packages The caret package receives over 38,000 direct downloads monthly making it one of the most popular packages in the R community. With that comes significant benefits including an abundant amount of documentation and helpful tutorials. You can install the Rdocumentation package to access helpful documentation and community examples directly in your R console. Simply copy and paste the following code: # Install and load RDocumentation for comprehensive help with R packages and functions install.packages("RDocumentation") library("RDocumentation") Of course, another benefit of learning a widely used package is that your colleagues are also likely using caret in their work - meaning you can collaborate on projects more easily. Additionally, caret is a dependent package for a large amount of additional machine learning and modeling packages as well. Understanding how caret works will make it easier and more fluid to learn even more helpful R packages. 3. It's easy to learn, but very powerful If you are a beginner R user, the caret package provides an easy interface for performing complex tasks. For example, you can train multiple different types of models with one easy, convenient format. You can also monitor various combinations of parameters and evaluate performance to understand their impact on the model you are trying to build. Additionally, the caret package helps you decide the most suitable model by comparing their accuracy and performance for a specific problem. Complete the code challenge below to see just how easy it is to to build models and predict values with caret. We've already gone ahead and split the mtcars dataset into a training set, train, and a test set,test. Both of these objects are available in the console. Your goal is to predict the miles per gallon of each car in the test dataset based on their weight. See for yourself how the caret package can handle this task with just two lines of code! 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 Want to learn it for yourself? You're in luck! DataCamp just released a brand new Machine Learning Toolbox course. The course is taught by co-authors of the caret package, Max Kuhn and Zachary Deane-Mayer. You'll be learning directly from the people who wrote the package through 24 videos and 88 interactive exercises. The course also includes a customer churn case study that let's you put your caret skills to the test and gain practical machine learning experience. What are you waiting for? Take the course now!

Create Air Travel Route Maps that look like airline route maps you find in aeroplane magazines using ggplot. Spatially visualise your travel diary. Continue reading → The post Create Air Travel Route Maps in ggplot: A Visual Travel Diary appeared first on The Devil is in the Data.

On occasion of the 10,000th R package on CRAN, eoda operated an automated Twitter account which regularly posted the current number of packages available on CRAN until the 10,000-package milestone has been passed on January 28, 2017. #Rstatsgoes10k – Hello World, it’s 2017-01-28 01:59:03 and currently there are 10000 packages on CRAN. — eodacelebratesR (@Rstatsgoes10k) … „Tutorial: How to set up a Twitter bot using R“ weiterlesen

With roots dating back to at least 1662 when John Graunt, a London merchant, published an extensive set of inferences based on mortality records, survival analysis is one of the oldest subfields of Statistics [1]. Basic life-table methods, including techniques for dealing with censored data, were discovered before 1700 [2], and in the early eighteenth century, the old masters - de Moivre working on annuities, and Daniel Bernoulli studying competing risks for the analysis of smallpox inoculation - developed the modern foundations of the field [2]. Today, survival analysis models are important in Engineering, Insurance, Marketing, Medicine, and many more application areas. So, it is not surprising that R should be rich in survival analysis functions. CRAN’s Survival Analysis Task View, a curated list of the best relevant R survival analysis packages and functions, is indeed formidable. We all owe a great deal of gratitude to Arthur Allignol and Aurielien Latouche, the task view maintainers. Looking at the Task View on a small screen, however, is a bit like standing too close to a brick wall - left-right, up-down, bricks all around. It is a fantastic edifice that gives some idea of the significant contributions R developers have made both to the theory and practice of Survival Analysis. As well-organized as it is, however, I imagine that even survival analysis experts need some time to find their way around this task view. Newcomers - people either new to R or new to survival analysis or both - must find it overwhelming. So, it is with newcomers in mind that I offer the following narrow trajectory through the task view that relies on just a few packages: survival, ggplot2, ggfortify, and ranger The survival package is the cornerstone of the entire R survival analysis edifice. Not only is the package itself rich in features, but the object created by the Surv() function, which contains failure time and censoring information, is the basic survival analysis data structure in R. Dr. Terry Therneau, the package author, began working on the survival package in 1986. The first public release, in late 1989, used the Statlib service hosted by Carnegie Mellon University. Thereafter, the package was incorporated directly into Splus, and subsequently into R. ggfortify enables producing handsome, one-line survival plots with ggplot2::autoplot. ranger might be the surprise in my very short list of survival packages. The ranger() function is well-known for being a fast implementation of the Random Forests algorithm for building ensembles of classification and regression trees. But ranger() also works with survival data. Benchmarks indicate that ranger() is suitable for building time-to-event models with the large, high-dimensional data sets important to internet marketing applications. Since ranger() uses standard Surv() survival objects, it’s an ideal tool for getting acquainted with survival analysis in this machine-learning age. Load the data This first block of code loads the required packages, along with the veteran dataset from the survival package that contains data from a two-treatment, randomized trial for lung cancer. library(survival) library(ranger) library(ggplot2) library(dplyr) library(ggfortify) #------------ data(veteran) head(veteran) ## trt celltype time status karno diagtime age prior ## 1 1 squamous 72 1 60 7 69 0 ## 2 1 squamous 411 1 70 5 64 10 ## 3 1 squamous 228 1 60 3 38 0 ## 4 1 squamous 126 1 60 9 63 10 ## 5 1 squamous 118 1 70 11 65 10 ## 6 1 squamous 10 1 20 5 49 0 The variables in veteran are: * trt: 1=standard 2=test * celltype: 1=squamous, 2=small cell, 3=adeno, 4=large * time: survival time in days * status: censoring status * karno: Karnofsky performance score (100=good) * diagtime: months from diagnosis to randomization * age: in years * prior: prior therapy 0=no, 10=yes Kaplan Meier Analysis The first thing to do is to use Surv() to build the standard survival object. The variable time records survival time; status indicates whether the patient’s death was observed (status = 1) or that survival time was censored (status = 0). Note that a “+” after the time in the print out of km indicates censoring. # Kaplan Meier Survival Curve km

Are you interested in guest posting? Publish at DataScience+ via your editor (i.e., RStudio). Category Advanced Modeling Tags Data Visualisation GLMM Logistic Regression R Programming spatial model Many datasets these days are collected at different locations over space which may generate spatial dependence. Spatial dependence (observation close together are more correlated than those further apart) violate the assumption of independence of the residuals in regression models and require the use of a special class of models to draw the valid inference. The […]Related Post Find the best predictive model using R/caret package/modelgrid Variable Selection Methods: Lasso and Ridge Regression in Python Bootstrap with Monte Carlo Simulation in Python Monte Carlo Simulation and Statistical Probability Distributions in Python K-Nearest Neighbors (KNN) with Python

This is to continue on the topic of using the melt/cast functions in reshape to convert between long and wide format of data frame. Here is the example I found helpful in generating covariate table required for PEER (or Matrix_eQTL) analysis:Here ...

This tutorial was prepared for the Ninth Annual Midwest Graduate Student Summit on Applied Economics, Regional, and Urban Studies (AERUS) on April 23rd-24th, 2016 at the University of Illinois at Urbana Champaign.

This book is for anyone looking to do forensic science analysis in a data-driven and open way.

A complete guide to data exploration in R explains how to read data sets in R, explore data in R, impute missing values in your dataset, merge in R, etc

MongoDB is a NoSQL database program which uses JSON-like documents with schemas. It is free and open-source cross-platform database. MongoDB, top NoSQL database engine in use today, could be a good data storage alternative when analyzing large volume data. To use MongoDB with R, first, we have to download and install MongoDB Next, start MongoDB. […]Related PostFinding Optimal Number of ClustersAnalyzing the first Presidential DebateGoodReads: Machine Learning (Part 3)Machine Learning for Drug Adverse Event DiscoveryGoodReads: Exploratory data analysis and sentiment analysis (Part 2)

Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.

Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.

apply function r, apply r, lapply r, sapply r, tapply r

I had a feeling that R has developed as a language to such a degree that many of us are using it now in completely different ways. This means that there are likely to be numerous tricks, packages, functions, etc that each of us use, but that others are completely…

A book for Spatial Statistics for Data Science with R.

Introduction Ever felt those data points were a bit too jittery? Smoothing out trends and revealing underlying patterns is a breeze with rolling averages in R. Ready to roll? Let’s dive in! Rolling with the ‘zoo’ Meet the ‘zoo’ package, your t...

Hey guys, welcome back to my R-tips newsletter. In today’s R-tip, I’m sharing a super common data science task (one that saved me 20 hours per week)… You’re getting the cheat code to automating Google Sheets. Plus, I’m sharing exactly how I made this a...

Introduction As data scientists, being able to investigate and visualize the geographic...

To be successful as a Data Scientist, you’re often put in positions where you need to find groups within your data. One key business use-case is finding clusters of customers that behave similarly. And that’s a powerful skill that I’m going to help you...

On the method’s advantages and disadvantages, demonstrated with the synthdid package in R

Introduction Shiny is an R package that allows you to build interactive web applications using R code. TidyDensity is an R package that provides a tidyverse-style interface for working with probability density functions. In this tutorial, we’ll ...

Just some simple codes to illustrate some points we will discuss this week, for the last course on GLMs, before the final exam. We have mentioned that the Gamma distribution belongs to the exponential, so we can run a regression, and compute the associated AIC, > set.seed(123) > test.data = rgamma(n=2000, scale=1, shape=1) > m1 = glm( test.data~1, family=Gamma(link=log)) > AIC(m1) [1] 3997.332 The Gamma distribution is also a special case of the Tweedie distribution, with power 2 > library(statmod) > library(tweedie) > m2 … Continue reading Model selection, AIC and Tweedie regression →

Nicolas Nguyen works in the Supply Chain industry, in the area of Demand and Supply Planning, S&OP and Analytics, where he enjoys developing solutions using R and Shiny. Outside his job, he teaches data visualization in R at the Engineering School EIGSI and Business School Excelia in the city of La Rochelle, France. Introduction Demand & Supply Planning requires forecasting techniques to determine the inventory needed to fulfill future orders. With R, we can build end-to-end supply chain monitoring processes to identify potential issues and run scenario testing. In a 3-part series, I will walk through a Demand & Supply Planning workflow: Using R in Inventory Management and Demand Forecasting: an introduction of projected inventory and coverage methodology (this post) Analyzing Projected Inventory Calculations Using R: an analysis of a demo dataset using the planr package Visualizing Projected Calculations with reactable and shiny: once the analysis is done, how would you present your results to your boss? By the end of the series, you will understand how and why to use R for Demand & Supply Planning calculations. Let’s begin! The “problem” we aim to solve When we work in Demand & Supply Planning, it’s pretty common that we need to calculate projected inventories (and related projected coverages). We often have three options to perform this calculation, using: an APS (Advanced Planning System) software an ERP, such as SAP or JDE and of course…Excel! All are fine and have different pros and cons. For example, we simply sometimes don’t have all the data in our ERP either APS, like when we work with third-party distributors or we want to model a supply chain network that relies on different systems with unconnected data. How about using R to perform these calculations? How simple and fast could they be? And, could we do more than just the calculations? For example, could we get an analysis of the projected situation of a portfolio (as an output of a function), so we don’t have to look at each product one by one and can instead: Easily get a summary view of the portfolio? Then zoom on the products with risks of shortages or overstocks? In a series of posts, I will demonstrate how R can help us in Demand & Supply planning. This first post introduces the proj_inv() and light_proj_inv() functions for projected inventory and coverage calculations. proj_inv(): to calculate projected inventories and coverages with some analysis features light_proj_inv(): to calculate projected inventories and coverages (only) Runs faster than the previous function (as it’s lighter and doesn’t provide any analysis features) With R, we have an efficient way to run end-to-end supply chain monitoring processes. Methodology How to calculate projected inventories First, let’s have a look at an example of how to calculate projected inventories. Consider that the field Demand = Sales Forecasts. We start with some Opening Inventory of 1000 units. During month M, we sell 100 units (the Demand). At the end of the 1st period (Month M), the inventory is 900 units. Then, there’s a demand of 800 units at the end of the following period (Month M+1). During the period (Month M+2), we get a Supply of 400 units, and sell 100: it is now 1100 units in stock. That’s all, this is how we calculate projected inventories ☺ Figure 1: Describes the mechanism of the calculation of projected inventories based on Opening Inventories, Demand and Supply How to calculate projected coverages Now, let’s have a look at how to calculate projected coverages. The idea: we look forward. We consider the projected inventories at the end of a period and evaluate the related coverage based on the Upcoming Demand. See the example below: Figure 2: Description of the calculation of projected coverages, considering the inventories at a point in time and the Upcoming Demand If we use Excel, we often see a “shortcut” to estimate the related coverages, like considering an average of the Demand over the next 3 or 6 months. This can lead to incorrect results if the Demand is not constant (if we have some seasonality or a strong trend, for example). However, these calculations become very easy through the proj_inv() and light_proj_inv() functions. Projected inventory calculations in R Now, let’s see how the above is done using two functions from the planr package. First, let’s create a tibble of data for the example shown above (we will cover Min.Stocks.Coverage and Max.Stocks.Coverage more thoroughly in another post): # Install the planr package # remotes::install_github("nguyennico/planr") library(planr) library(dplyr) Planr_Example % select(Projected.Inventories.Qty) ## # A tibble: 7 × 2 ## # Groups: DFU [1] ## DFU Projected.Inventories.Qty ## ## 1 Item0001 900 ## 2 Item0001 800 ## 3 Item0001 1100 ## 4 Item0001 300 ## 5 Item0001 200 ## 6 Item0001 -100 ## 7 Item0001 200 We can also take a look at projected coverage. It matches our example calculation in Figure 2: the opening coverage is 2.9 months. Calculated_Inv %>% select(Calculated.Coverage.in.Periods) ## # A tibble: 7 × 2 ## # Groups: DFU [1] ## DFU Calculated.Coverage.in.Periods ## ## 1 Item0001 2.9 ## 2 Item0001 1.9 ## 3 Item0001 2.7 ## 4 Item0001 1.7 ## 5 Item0001 0.7 ## 6 Item0001 0 ## 7 Item0001 99 Very easy to calculate! The proj_inv() and light_proj_inv() functions can also be used and combined to perform more complex tasks. I’ve described several use cases in the appendix. Moving forward, these functions form the basis for the classic DRP (Distribution Requirement Planning) calculation, where, based on some parameters (usually minimum and maximum levels of stock, a reorder quantity, and a frozen horizon), we calculate a Replenishment Plan. Conclusion Thank you for reading this introduction of projected inventories and coverages in Demand & Supply Planning! I hope that you enjoyed reading how this methodology translate into R. ASCM (formerly APICS) guidelines In the beginning of 2019, the Association for Supply Chain Management (ASCM) published an article about the usage of R (and Python) in Supply Chain Planning, and more precisely for the Sales & Operations Planning (S&OP) process, which is related to Demand and Supply Planning. Figure 3: An extract from the ASCM article regarding the S&OP and Digital Supply Chain. It shows how R and Python are becoming more and more used for demand & supply planning and are great tools to run a S&OP process. In the example above, we can see how R helps build the digital environment useful to run the S&OP process, which involves a lot of data processing. The planr package aims to support this process by providing functions that calculate projected inventories. Stay tuned for more on projected calculations using R Thank you for reading the introduction on how to use R for projected inventory calculations in Demand & Supply Planning! I hope you enjoyed this introduction to the planr package. My series of posts will continue with: Analyzing Projected Calculations Using R (using a demo dataset) Visualizing Projected Calculations with reactable and Shiny (or, what your boss wants to see) In the meantime, check out these useful links: planr package GitHub repository: https://github.com/nguyennico/planr URL for a Shiny app showing a demo of the proj_inv() and light_proj_inv() functions: Demo: app proj_inv() function (shinyapps.io) Appendix: Use cases and examples The proj_inv() and light_proj_inv() functions can easily be used and combined to perform more complex tasks, such as: Modeling of a Supply Chain Network Calculation of projected inventories from Raw Materials to Finished Goods A multi-echelon distribution network: from a National Distribution Center to Regional Wholesalers to Retailers Becoming a useful tool: To build an End-to-End Supply Chain monitoring process To support the S&OP (Sales and Operations Planning) process, allowing us to run some scenarios quickly: Change of Sales plan Change of Supply (Production) plan Change of stock level parameters Change of Transit Time Etc. Here are some detailed use cases for the functions. Third-party distributors We sometimes work with third-party distributors to distribute our products. A common question is: how much stock do our partners hold? If we have access to their opening inventories and Sales IN & OUT Forecasts, we can quickly calculate the projected inventories by applying the proj_inv() or light_proj_inv() functions. Then, we anticipate any risks of shortages or overstocks, and create a collaborative workflow. Figure 4: Illustration of a SiSo (Sales IN Sales OUT) situation. We have some stocks held at a storage location, for example, a third-party distributor, and know what will be sold out of this location (the sales out) and what will be replenished to it (the sales in), as well as the opening inventory. The aim is to calculate the projected inventories and coverages at this location. From raw materials to finished goods In the example below, we produce olive oil (but it could be shampoo, liquor, etc.). We start with a raw material, the olive oil, that we use to fill up different sizes of bottles (35cl, 50cl, etc…), on which we then apply (stick) a label (and back label). There are different labels, depending on the languages (markets where the products are sold). Once we have a labelled bottle, we put it inside an outer box, ready to be shipped and sold. There are different dimensions of outer boxes, where we can put, for examplem 4, 6 or 12 bottles. They are the Finished Goods. We have two groups of products here: Finished Goods Semi-Finished: at different steps, filled bottle (not yet labelled) or labelled bottle We might be interested in looking at the projected inventories at different levels / steps of the manufacturing process: Finished Goods Raw Materials: naked bottles, labels, or liquid (olive oil) Semi-Finished Products For this, we can apply the proj_inv() or light_proj_inv() functions on each level of analysis. Figure 5...

Learn how to design beautiful tables in R! Join our workshop on Designing Beautiful Tables in R which is a part of our workshops for Ukraine series. Here’s some more info: Title: Designing Beautiful Tables in R Date: Thursday, April 27th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) Speaker: Tanya Shapiro is a freelance … Continue reading Designing Beautiful Tables in RDesigning Beautiful Tables in R was first posted on March 25, 2023 at 3:28 pm.

This thesis consists of two main projects and a third project which is provided in the appendix. The contribution of the first project, is a tool set for parallel random number gen- eration on GPUs…

Nothing short of wacky usage of plot() function with xspline to interpolate the points, but still a “parameter” short of Bezier’s curve. 🙂 Given two random vectors, you can generate a plot that, xspline will smooth out the plot and…Read more ›

It’s March 2023 and right now ChatGPT, the amazing AI chatbot tool from OpenAI, is all the rage. But when OpenAI released their public web API for ChatGPT on the 1st of March you might have been a bit disappointed. If you’re an R user, that is. Because, when scrolling through the release announcement you find that there is a python package to use this new API, but no R package. I’m here to say: Don’t be disappointed! As long as there is a web API for a service then it’s going to be easy to use this service from R, no specialized package needed. So here’s an example of how to use the new (as of March 2023) ChatGPT API from R. But know that when the next AI API hotness comes out (likely April 2023, or so) then it’s going to be easy to interface with that from R, as well. Calling the ChatGPT web API from R To use the ChatGPT API in any way you first need to sign up and get an API key: The “password” you need to access the web API. It could look something like "sk-5xWWxmbnJvbWU4-M212Z2g5dzlu-MzhucmI5Yj-l4c2RkdmZ26". Of course, that’s not my real API key because that’s something you should keep secret! With an API key at hand you now look up the documentation and learn that this is how you would send a request to the API from the terminal: curl https://api.openai.com/v1/chat/completions \ -H "Authorization: Bearer $OPENAI_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "What is a banana?"}] }' But how do we send a request to the API using R? What we can do is to “replicate” this call using httr: a popular R package to send HTTP requests. Here’s how this request would be made using httr (with the curl lines as comments above the corresponding httr code) library(httr) api_key

The article talks about R packages with a range of functions, including data manipulation, data visualization, machine learning, etc.

A consistent, simple and easy to use set of wrappers around the fantastic 'stringi' package. All function and argument names (and positions) are consistent, all functions deal with "NA"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.

The goal of 'readr' is to provide a fast and friendly way to read rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed to flexibly parse many types of data found in the wild, while still cleanly failing when data unexpectedly changes.

A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

A practical introduction.

OpenStreetMap + Data Visualization = Art

If there’s one type of data no company has a shortage of, it has to be time series data. Yet, many beginner and intermediate R developers struggle to grasp their heads around basic R time series concepts, such as manipulating datetime values, visualizing time data over time, and handling missing date values. Lucky for you, […] The post appeared first on appsilon.com/blog/.

Learn the basic steps to run a Multiple Correspondence Analysis in R

3rd edition

At the EEX, German baseload electricity futures for the year 2023 trade at a price of 950 Euro / MWh and peak load futures at 1275 Euro / MWh. Future prices for France are even higher. (Prices were looked up on 2022-08-28). In contrast, average German...

Effective interactive data visualizations in R

This article will dive into R's different uses and demonstrate what you can do with this programming language once you've learned it.

A technical manual of graphs, networks and their applications in the people and social sciences

Leverage the powerful data wrangling tools in R’s dplyr to clean and prepare your data.

Making a survival analysis can be a challenge even for experienced R users, but the good news is I’ll help you make beautiful, publication-quality survival plots in under 10-minutes. Here’s what WE are going to do: Make your first survival model an...

An extremely long review of R.

This cookbook contains more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly—without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a discussion of how and why the recipe works.

A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools

R graphics tutorial: scatterplots with anti-aliasing, using the Cairo library. Two lines of code to make much better visualizations in R.

R kernel for Jupyter.

In January 2016, I was honored to receive an “Honorable Mention” of the John Chambers Award 2016. This article was written for R-bloggers, whose builder, Tal Galili, kindly invited me to write an introduction to the rARPACK package. A Short Story of rARPACK Eigenvalue decomposition is a commonly used technique in numerous statistical problems. For example, principal component analysis (PCA) basically conducts eigenvalue decomposition on the sample covariance of a data matrix: the eigenvalues are the component variances, and eigenvectors are the variable loadings. In R, the standard way to compute eigenvalues is the eigen() function. However, when the matrix becomes large, eigen() can be very time-consuming: the complexity to calculate all eigenvalues of a $n times n$ matrix is $O(n^3)$. While in real applications, we usually only need to compute a few eigenvalues or eigenvectors, for example to visualize high dimensional data using PCA, we may only use the first two or three components to draw a scatterplot. Unfortunately in eigen(), there is no option to limit the number of eigenvalues to be computed. This means that we always need to do the full eigen decomposition, which can cause a huge waste in computation. And this is why the rARPACK package was developed. As the name indicates, rARPACK was originally an R wrapper of the ARPACK library, a FORTRAN package that is used to calculate a few eigenvalues of a square matrix. However ARPACK has stopped development for a long time, and it has some compatibility issues with the current version of LAPACK. Therefore to maintain rARPACK in a good state, I wrote a new backend for rARPACK, and that is the C++ library Spectra. The name of rARPACK was POORLY designed, I admit. Starting from version 0.8-0, rARPACK no longer relies on ARPACK, but due to CRAN polices and reverse dependence, I have to keep using the old name. Features and Usage The usage of rARPACK is simple. If you want to calculate some eigenvalues of a square matrix A, just call the function eigs() and tells it how many eigenvalues you want (argument k), and which eigenvalues to calculate (argument which). By default, which = "LM" means to pick the eigenvalues with the largest magnitude (modulus for complex numbers and absolute value for real numbers). If the matrix is known to be symmetric, calling eigs_sym() is preferred since it guarantees that the eigenvalues are real. library(rARPACK) set.seed(123) ## Some random data x = matrix(rnorm(1000 * 100), 1000) ## If retvec == FALSE, we don't calculate eigenvectors eigs_sym(cov(x), k = 5, which = "LM", opts = list(retvec = FALSE)) For really large data, the matrix is usually in sparse form. rARPACK supports several sparse matrix types defined in the Matrix package, and you can even pass an implicit matrix defined by a function to eigs(). See ?rARPACK::eigs for details. library(Matrix) spmat = as(cov(x), "dgCMatrix") eigs_sym(spmat, 2) ## Implicitly define the matrix by a function that calculates A %*% x ## Below represents a diagonal matrix diag(c(1:10)) fmat = function(x, args) { return(x * (1:10)) } eigs_sym(fmat, 3, n = 10, args = NULL) From Eigenvalue to SVD An extension to eigenvalue decomposition is the singular value decomposition (SVD), which works for general rectangular matrices. Still take PCA as an example. To calculate variable loadings, we can perform an SVD on the centered data matrix, and the loadings will be contained in the right singular vectors. This method avoids computing the covariance matrix, and is generally more stable and accurate than using cov() and eigen(). Similar to eigs(), rARPACK provides the function svds() to conduct partial SVD, meaning that only part of the singular pairs (values and vectors) are to be computed. Below shows an example that computes the first three PCs of a 2000x500 matrix, and I compare the timings of three different algorithms: library(microbenchmark) set.seed(123) ## Some random data x = matrix(rnorm(2000 * 500), 2000) pc = function(x, k) { ## First center data xc = scale(x, center = TRUE, scale = FALSE) ## Partial SVD decomp = svds(xc, k, nu = 0, nv = k) return(list(loadings = decomp$v, scores = xc %*% decomp$v)) } microbenchmark(princomp(x), prcomp(x), pc(x, 3), times = 5) The princomp() and prcomp() functions are the standard approaches in R to do PCA, which will call eigen() and svd() respectively. On my machine (Fedora Linux 23, R 3.2.3 with optimized single-threaded OpenBLAS), the timing results are as follows: Unit: milliseconds expr min lq mean median uq max neval princomp(x) 274.7621 276.1187 304.3067 288.7990 289.5324 392.3211 5 prcomp(x) 306.4675 391.9723 408.9141 396.8029 397.3183 552.0093 5 pc(x, 3) 162.2127 163.0465 188.3369 163.3839 186.1554 266.8859 5 Applications SVD has some interesting applications, and one of them is image compression. The basic idea is to perform a partial SVD on the image matrix, and then recover it using the calculated singular values and singular vectors. Below shows an image of size 622x1000: (Orignal image) If we use the first five singular pairs to recover the image, then we need to store 8115 elements, which is only 1.3% of the original data size. The recovered image will look like below: (5 singular pairs) Even if the recovered image is quite blurred, it already reveals the main structure of the original image. And if we increase the number of singular pairs to 50, then the difference is almost imperceptible, as is shown below. (50 singular pairs) There is also a nice Shiny App developed by Nan Xiao, Yihui Xie and Tong He that allows users to upload an image and visualize the effect of compression using this algorithm. The code is available on GitHub. Performance Finally, I would like to use some benchmark results to show the performance of rARPACK. As far as I know, there are very few packages available in R that can do the partial eigenvalue decomposition, so the results here are based on partial SVD. The first plot compares different SVD functions on a 1000x500 matrix, with dense format on the left panel, and sparse format on the right. The second plot shows the results on a 5000x2500 matrix. The functions used corresponding to the axis labels are as follows: svd: svd() from base R, which computes the full SVD irlba: irlba() from irlba package, partial SVD propack, trlan: propack.svd() and trlan.svd() from svd package, partial SVD svds: svds() from rARPACK The code for benchmark and the environment to run the code can be found here.

Powerful R libraries built by the World’s Biggest Tech Companies

Way back in August 2020, I launched Big Book of R, a collection of free (and some paid) R programming books organised by categories like Geospatial, Statistics, Packages and many more. What started off as a 100 book collection has now grown to over 200 :D! Anyway, I felt was … The post Big Book of R has over 200 books! appeared first on Oscar Baruffa.

This is a draft of a book for learning data analysis with the R language. This book emphasizes hands activities. Comments and suggestions are welcome.

Note. This is an update to article: Using R and H2O to identify product anomalies during the manufacturing process.It has some updates but also code optimization from Yana Kane-Esrig( https://www.linkedin.com/in/ykaneesrig/ ), as sh...

An illustrative guide to estimate the pure premium using Tweedie models in GLMs and Machine Learning

A kind reader recently shared the following comment on the Practical Data Science with R 2nd Edition live-site. Thanks for the chapter on data frames and data.tables. It has helped me overcome an o…

Isotonic regression is a method for obtaining a monotonic fit for 1-dimensional data. Let’s say we have data such that . (We assume no ties among the ‘s for simplicity.) Informally, isotonic regression looks for such that the ‘s approximate … Continue reading →

Case study of tweets from comments on Indonesia’s biggest media

Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency.

Vector Indexing, Eigenvector Solvers, Singular Value Decomposition, & More

Practical Data Science with R, 2nd Edition author Dr. Nina Zumel, with a fresh author’s copy of her book!

The timekit package contains a collection of tools for working with time series in R. There’s a number of benefits. One of the biggest is the ability to use a time series signature to predict future values (forecast) through data mining techniques. W...

Operations need to have demand forecasts in order to establish optimal resource allocation policies. But, when we make predictions the only thing that we assure is the occurrence of prediction errors. Fortunately, there is no need to be 100% accurate to succeed, we just need to perform better than our competitors. In this exercise we […] Related exercise sets:Forecasting: Exponential Smoothing Exercises (Part-3) Forecasting for small business Exercises (Part-3) Forecasting: Time Series Exploration Exercises (Part-1) Explore all our (>1000) R exercisesFind an R course using our R Course Finder directory

Building machine learning and statistical models often requires pre- and post-transformation of the input and/or response variables, prior to training (or fitting) the models. For example, a model may require training on the logarithm of the response and input variables. As a consequence, fitting and then generating predictions from these models requires repeated application of … Continue reading

Learn R through 1000+ free exercises on basic R concepts, data cleaning, modeling, machine learning, and visualization.

Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.

This article comes from Togaware. A Survival Guide to Data Science with R These draft chapters weave together a collection of tools for the data scientist—tools that are all part of the R Statistical Software Suite. Each chapter is a  collection of one (or more) pages that cover particular aspects of the topic. The chapters can be… Read More »One-page R: a survival guide to data science with R

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Last week, I had the opportunity to talk to a group of Master’s level Statistics and Business Analytics students at Cal State East Bay about R and Data Science. Many in my audience were adult students coming back to school with job experience writing code in Java, Python and SAS. It was a pretty sophisticated crowd, but not surprisingly, their R skills were stitched together in a way that left some big gaps.

Stefan Feuerriegel This blog entry concerns our course on “Operations Reserch with R” that we teach as part of our study program. We hope that the materials are of value to lectures and everyone else working in the field of numerical optimiatzion. Course outline The course starts with a review of numerical and linear algebra … Continue reading "Operations Research with R"

R Language Tutorials for Advanced Statistics

If you have tried to communicate research results and data visualizations using R, there is a good chance you will have come across one of its great limitations. R is painful when you need to...

We will review another fascinating approach that marries heuristic and probabilistic methods. We will link marketing channels with a probability of a customer passing through each step of a Sales Funnel

Release 1.4 of the magick package introduces a new feature called image convolution that was requested by Thomas L. Pedersen. In this post we explain what this is all about. Kernel Matrix The new image_convolve() function applies a kernel over the image. Kernel convolution means that each pixel value is recalculated using the weighted neighborhood sum defined in the kernel matrix. For example lets look at this simple kernel: library(magick) kern % image_negate() As with the blurring, the original image can be blended in with the transformed one, effectively sharpening the image along edges. img %>% image_convolve('DoG:0,0,2', scaling = '100, 100%') The ImageMagick documentation has more examples of convolve with various avaiable kernels.

Sentiment Analysis is one of the most obvious things Data Analysts with unlabelled Text data (with no score or no rating) end up doing in an attempt to extract some insights out of it and the same Sentiment analysis is also one of the potential research areas for any NLP (Natural Language Processing) enthusiasts. For […] Related Post Creating Reporting Template with Glue in R Predict Employee Turnover With Python Making a Shiny dashboard using ‘highcharter’ – Analyzing Inflation Rates Time Series Analysis in R Part 2: Time Series Transformations Time Series Analysis in R Part 1: The Time Series Object

‘ImageMagick’ is one of the famous open source libraries available for editing and manipulating Images of different types (Raster & Vector Images). magick is an R-package binding to ‘ImageMagick’ for Advanced Image-Processing in R, authored by Jeroen Ooms. magick supports many common image formats like png, jpeg, tiff and manipulations like rotate, scale, crop, trim, […] Related Post Analyzing the Bible and the Quran using Spark Predict Customer Churn – Logistic Regression, Decision Tree and Random Forest Find Your Best Customers with Customer Segmentation in Python Principal Component Analysis – Unsupervised Learning ARIMA models and Intervention Analysis

Lately I’ve been thinking a lot about the connection between prediction models and the decisions that they influence. There is a lot of theory around this, but communicating how the various pieces all fit together with the folks who will use and be impacted by these decisions can be challenging. One of the important conceptual pieces […]

A tutorial for using ggmap to plot basic maps in R, by using images from Google Maps as a ggplot layer.

We have been writing a lot on higher-order data transforms lately: Coordinatized Data: A Fluid Data Specification Data Wrangling at Scale Fluid Data Big Data Transforms. What I want to do now is "write a bit more, so I finally feel I have been concise." The cdata R package supplies general data transform operators. The … Continue reading Arbitrary Data Transforms Using cdata

Which layout of an advertisement leads to more clicks? Would a different color or position of the purchase button lead to a higher conversion rate? Does a special offer really attract more customers – and which of two phrasings would be better? For a long time, people have trusted their gut feeling to answer these questions. Today all these questions could be answered by conducting an A/B test. For this purpose, visitors of a website are randomly assigned to one of two groups between which the target metric (i.e. click-through rate, conversion rate…) can then be compared. Due to this randomization, the groups do not systematically differ in all other relevant dimensions. This means: If your target metric takes a significantly higher value in one group, you can be quite sure that it is because of your treatment and not because of any other variable. In comparison to other methods, conducting an A/B test does not require extensive statistical knowledge. Nevertheless, some caveats have to be taken into account. When making a statistical decision, there are two possible errors (see also table 1): A Type I error means that we observe a significant result although there is no real difference between our groups. A Type II error means that we do not observe a significant result although there is in fact a difference. The Type I error can be controlled and set to a fixed number in advance, e.g., at 5%, often denoted as α or the significance level. The Type II error in contrast cannot be controlled directly. It decreases with the sample size and the magnitude of the actual effect. When, for example, one of the designs performs way better than the other one, it’s more likely that the difference is actually detected by the test in comparison to a situation where there is only a small difference with respect to the target metric. Therefore, the required sample size can be computed in advance, given α and the minimum effect size you want to be able to detect (statistical power analysis). Knowing the average traffic on the website you can get a rough idea of the time you have to wait for the test to complete. Setting the rule for the end of the test in advance is often called “fixed-horizon testing”. Table 1: Overview over possible errors and correct decisions in statistical tests Effect really exists No Yes Statistical test is significant No True negative Type II error (false negative) Yes Type I error (false positive) True positive Statistical tests generally provide the p-value which reflects the probability of obtaining the observed result (or an even more extreme one) just by chance, given that there is no effect. If the p-value is smaller than α, the result is denoted as “significant”. When running an A/B test you may not always want to wait until the end but take a look from time to time to see how the test performs. What if you suddenly observe that your p-value has already fallen below your significance level – doesn’t that mean that the winner has already been identified and you could stop the test? Although this conclusion is very appealing, it can also be very wrong. The p-value fluctuates strongly during the experiment and even if the p-value at the end of the fixed-horizon is substantially larger than α, it can go below α at some point during the experiment. This is the reason why looking at your p-value several times is a little bit like cheating, because it makes your actual probability of a Type I error substantially larger than the α you chose in advance. This is called “α inflation”. At best you only change the color or position of a button although it does not have any impact. At worst, your company provides a special offer which causes costs but actually no gain. The more often you check your p-value during the data collection, the more likely you are to draw wrong conclusions. In short: As attractive as it may seem, don’t stop your A/B test early just because you are observing a significant result. In fact you can prove that if you increase your time horizon to infinity, you are guaranteed to get a significant p-value at some point in time. The following code simulates some data and plots the course of the p-value during the test. (For the first samples which are still very small R returns a warning that the chi square approximation may be incorrect.) library(timeDate) library(ggplot2) # Choose parameters: pA

It can be found on the RStudio cheatsheet page. Suggestions and pull requests are always welcome.

Discover which statistical methods dominate healthcare, finance, tech, retail, and sports analytics, and why these industry-method pairings became indispensable standards.

A/B testing is a cornerstone of data science, essential for making informed business decisions and optimizing customer revenue. Here, we delve into six widely used statistical methods in A/B testing, explaining their purposes and appropriate contexts. 1. Z-Test (Standard Score Test): When to Use: This method is ideal for large sample sizes (typically over 30) when the population variance is known. Purpose: Compares the means of two groups to determine if they are statistically different. Applications: This technique is frequently employed in conversion rate optimization and click-through rate analysis. It helps identify whether changes in website elements or marketing strategies

Pic by author - using DALL-E 3 When running experiments don’t forget to bring your survival kit I’ve already made the case in several blog posts (part 1, part 2, part 3) that using survival analysis can improve churn prediction. In this blog post I’ll ...

Visual, interactive sample size calculator ideal for planning online experiments and A/B tests.

A deep-dive into how and why Statsmodels uses numerical optimization instead of closed-form formulas

Evaluating ad targeting product using causal inference: propensity score matching!

For non-tech industry folks, an “A/B test” is just a randomized controlled trial where you split users or other things into treatment and control groups, and then later compare key metr…

Running experiments is equal parts powerful and terrifying. Powerful because you can validate changes that will transform your product for the better…

An in-depth explanation of “Thompson Sampling”, a more efficient alternative to A/B testing for online learning

Questions on A/B testing are being increasingly asked in interviews but reliable resources to prepare for these are still far and few…

Using and choosing priors in randomized experiments.

A Discussion of the go-to methods for 5 Types of A/B Metrics

Cookies and privacy, interleaving experiments, clean dial-ups, and test metrics

How today’s tech companies make data-driven decisions in Machine Learning production

While Fisher’s exact test is a convenient tool for A/B testing, the idea and results of the test are often hard to grasp and difficult to…

A/B testing is hitting the mainstream because it is so effective. And with so many tools available it has become very easy and very inexpensive to run. Here are 23 helpful tips on how you can take your A/B tests from basic to the next level.

A/B tests provide more than statistical validation of one execution over another. They can and should impact how your team prioritizes projects.

We’re Agile, we think lean, we’re data-driven. If you live in the new economy and work in some sort of digital product you hear some of…

An applied introduction to causal inference in tech

We spoke with Etsy’s iOS Software Engineer, Lacy Rhoades, about their culture of continuous experimentation. Learn about their a/b testing culture

An in-depth guide to the state-of-the-art variance reduction technique for A/B tests

If you want to always be closing, then you need to always be testing, a long-standing mantra (and title of a popular book) in the search marketing space.

A/B testing is a very popular technique of checking granular changes in a product without mistakenly taking into account changes that were…

Multivariate tests indicate how various UI elements interact with each other and are a tool for making incremental improvements to a design.

Data will tell you the right answer. If you can’t find data somewhere, you should run a test, collect the data, and let it tell you what’s right. A/B testing is one of the core marketing arts a marketer should master and practice.

The best way to determine what works best for your site is to carry out an A/B test for your landing pages. Check out this A/B significant test calculator.

Our A/B test calculator will help you to compare two or three variants to determine which test will be statistically significant.

Elaborate usability tests are a waste of resources. The best results come from testing no more than 5 users and running as many small tests as you can afford.

A/B testing, the process of exposing randomized visitors to one or more variables, is among the most effective strategies to optimize user experiences and conversion rates. Here is a list of A/B testing tools.

Statistics & Business can share the same Language

Experimentation is widely used at tech startups to make decisions on whether to roll out new product features, UI design changes, marketing campaigns and more, usually with the goal of improving…

The best way to optimise your website is usually the simplest.

How not to fail your online controlled experimentation

Optimizing web marketing strategies through statistical testing

A/B Testing — A complete guide to statistical testing - bjpcjp/AB_Testing

The intuitive way of A/B testing. The advantages of the Bayesian approach and how to do it.

A/B testing is a very popular technique for checking granular changes in a product without mistakenly taking into account changes that…

This is a story of how a software company was able to start a conversation with 8x more of their users by cutting the length of their emails by 90%. You could set up a test of this method in less than an hour. The Problem One of the most

Part 2: Proportion Metrics

Making the most out of your experiments and observational data

Big success. Bigger failure. And lots of lessons. Learn why building a growth team may be a multi-million dollar mistake.

197K subscribers in the datasets community. A place to share, find, and discuss Datasets.

Etsy relies heavily on experimentation to improve our decision-making process. We leverage our internal A/B testing tool when...

The biggest question in ecommerce A/B testing is not “how.”

A/B tests are controlled experiments of two attributes, to measure which one was most popular with users. You can apply A/B testing to just about anything that you can measure. Multivariate testing allows you to measure multiple variables simultaneously.

Which layout of an advertisement leads to more clicks? Would a different color or position of the purchase button lead to a higher conversion rate? Does a special offer really attract more customers – and which of two phrasings would be better? For a long time, people have trusted their gut feeling to answer these questions. Today all these questions could be answered by conducting an A/B test. For this purpose, visitors of a website are randomly assigned to one of two groups between which the target metric (i.e. click-through rate, conversion rate…) can then be compared. Due to this randomization, the groups do not systematically differ in all other relevant dimensions. This means: If your target metric takes a significantly higher value in one group, you can be quite sure that it is because of your treatment and not because of any other variable. In comparison to other methods, conducting an A/B test does not require extensive statistical knowledge. Nevertheless, some caveats have to be taken into account. When making a statistical decision, there are two possible errors (see also table 1): A Type I error means that we observe a significant result although there is no real difference between our groups. A Type II error means that we do not observe a significant result although there is in fact a difference. The Type I error can be controlled and set to a fixed number in advance, e.g., at 5%, often denoted as α or the significance level. The Type II error in contrast cannot be controlled directly. It decreases with the sample size and the magnitude of the actual effect. When, for example, one of the designs performs way better than the other one, it’s more likely that the difference is actually detected by the test in comparison to a situation where there is only a small difference with respect to the target metric. Therefore, the required sample size can be computed in advance, given α and the minimum effect size you want to be able to detect (statistical power analysis). Knowing the average traffic on the website you can get a rough idea of the time you have to wait for the test to complete. Setting the rule for the end of the test in advance is often called “fixed-horizon testing”. Table 1: Overview over possible errors and correct decisions in statistical tests Effect really exists No Yes Statistical test is significant No True negative Type II error (false negative) Yes Type I error (false positive) True positive Statistical tests generally provide the p-value which reflects the probability of obtaining the observed result (or an even more extreme one) just by chance, given that there is no effect. If the p-value is smaller than α, the result is denoted as “significant”. When running an A/B test you may not always want to wait until the end but take a look from time to time to see how the test performs. What if you suddenly observe that your p-value has already fallen below your significance level – doesn’t that mean that the winner has already been identified and you could stop the test? Although this conclusion is very appealing, it can also be very wrong. The p-value fluctuates strongly during the experiment and even if the p-value at the end of the fixed-horizon is substantially larger than α, it can go below α at some point during the experiment. This is the reason why looking at your p-value several times is a little bit like cheating, because it makes your actual probability of a Type I error substantially larger than the α you chose in advance. This is called “α inflation”. At best you only change the color or position of a button although it does not have any impact. At worst, your company provides a special offer which causes costs but actually no gain. The more often you check your p-value during the data collection, the more likely you are to draw wrong conclusions. In short: As attractive as it may seem, don’t stop your A/B test early just because you are observing a significant result. In fact you can prove that if you increase your time horizon to infinity, you are guaranteed to get a significant p-value at some point in time. The following code simulates some data and plots the course of the p-value during the test. (For the first samples which are still very small R returns a warning that the chi square approximation may be incorrect.) library(timeDate) library(ggplot2) # Choose parameters: pA

Data Science, Machine Learning, AI & Analytics

Delroy Lindo already deserved an Oscar nomination. He might finally get one for his role as Delta Slim in Ryan Coogler's Sinners.

Marlon Brando has now been gone for more than two decades, and so thoroughgoing was his impact on the art of film acting that younger generations of movie-lovers may have trouble pinning down what, exactly, he did so differently on screen.

He was the world’s most famous child star. Then he had to figure out what came next.

Eastwood biographer Shawn Levy dives into the making of the director’s masterpiece: “Unforgiven was Clint Eastwood saying, ‘This is what I’m going to do…get out of my way.’”

The funniest people on the planet think there’s no funnier person than Albert Brooks.

The Matlock star talks candidly about longevity, mental health, and the decades she spent feeling like she didn’t belong.

In describing how they remember their lines, actors are telling us an important truth about memory.

The actor plays dual roles in 'Fallout'—a monster and the man he used to be—prompting a look back at his own unlikely past.

From 2008: What was real about the realest actor of them all? Claudia Roth Pierpont on Brando’s dilemmas and his depths.

Paul Giamatti’s performance in "The Holdovers" is just another high point in a long, memorable career.

A star since childhood, she spent decades guarding her privacy. On-screen, she’s always played the solitary woman under pressure. But in a pair of new roles, she’s revealed a different side of herself.

The world is finally singing her long-overdue praise.

We asked critics and Hollywood creators: Which supporting players make everything better?

After leaving L.A. and making only one public appearance since — on a widely condemned mental illness episode of 'Dr. Phil' — the complicated star of 'The Shining' discusses her legacy and the trauma of the Stanley Kubrick film.

From ‘Urban Cowboy’ to ‘Northern Exposure’ to ‘No Country for Old Men,’ Texas’s finest character actor isn’t hanging up his spurs just yet.

Although ‘Cheers’ made the actor a star, he always swore he had a tough time getting comfortable playing the womanizing character. But the humanity he brought to Sam has informed his career and his life ever since.

Why do we use the logistic and softmax functions? Thermal physics may have an answer.

Keep your neural network alive by understanding the downsides of ReLU

Activation functions are functions which take an input signal and convert it to an output signal. Activation functions introduce…

Recently, a colleague of mine asked me a few questions like “why do we have so many activation functions?”, “why is that one works better…

Activation functions are functions that we apply in neural networks after (typically) applying an affine transformation combining weights and input features. They are typically non-linear functions. The rectified linear unit, or ReLU, has been the most popular in the past decade, although the choice is architecture dependent and many alternatives have emerged in recent years. In this section, you will find a constantly updating list of activation functions.

The essence of non-linearity.

Week Two - 100 Days of Code Challenge

The purpose of this post is to provide guidance on which combination of final-layer activation function and loss function should be used in…

Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.

How silicon valley is putting a price tag on your attention - and relationships

OnlyFans leverages a meticulously crafted UX to create a powerful sense of intimacy and exclusivity, captivating users while sparking ethical debates about manipulation and exploitation.

How easy is it to fall into auction addiction? Here we examine how one site, Quibids, tried its hand at behavioral design.

Patients whose brain injury coincidentally relieved their nicotine cravings may help unravel the neural underpinnings of addiction, a new study suggests.

A couple of years ago, I decided I'd had enough of ads. Not just the occasional banner or a quick pre-roll video — I mean all of them. They have to go.

Do you know who you’re really competing against? Here's how the Google Ads Auction Insights report can give you a huge competitive advantage.

A new attribution approach uses large sets of anonymized data to infer which channels and campaigns led to conversions.

In this edition of our Confessions series, a growth marketing veteran explains why they’ve they pulled all ad dollars from Google's PMax.

Learn how to use Google Ads Keyword Planner — from finding high-impact keywords to understanding search volumes and forecasts.

The way Perplexity is sharing ad revenue with publishers depends on a number of factors. Here’s how Perplexity is making those calculations.

#60: Break Into Google Spanner Architecture (5 Minutes)

Digital advertising is developing at the speed of light, and things like Attekmi white label ad exchange are becoming an

The tech giant, which wrapped up its arguments in the federal monopoly trial, simply says it has the best product.

The final days of the trial approach.

Is such a thing possible for an industry that never respected people's wishes?

The third-largest US retailer is planning on rolling out targeted ad capabilities on and off its website.

Here's a methodology for identifying piracy sites making money with Google ads

How to dig into ad libraries from Google, Meta and other platforms to track spending, narratives, campaigns and more

Originally published Feb. 17, 2022

ID spoofing, cookie stuffing, ID stuffing, etc. What does it mean when an SSP's user ID doesn't match the DSP's ID?

Many ad executives have found Amazon's DSP to be cumbersome to use, lacking in measurement capabilities and limited in the range of inventory it offers for purchase.

The images offer a rare glimpse inside murky enterprises that artificially generate social media likes, comments and shares for less than a cent a click.

Meet the guy who taught US intelligence agencies how to make the most of the ad tech ecosystem, "the largest information-gathering enterprise ever conceived by man."

A deep dive into why the DOJ thinks RGSP makes ad auctions unfair, and why Google believes it creates a better user experience.

Jeff Bezos long shunned ads. However, Amazon's juicy first-party data has enabled it to compete with Alphabet and Meta in the new digital advertising landscape.

Google's targeted ad initiative AdSense was initially launched as “content targeting advertising” 20 years ago this month. Here’s how it changed the internet.

Getting started with Google Ads is a bit more complex than it used to be. This guide walks you through the initial steps of account setup.

Lost in the Sturm und Drang of Q4 (Q for quarantine) 2020, Google introduced a beta program called Performance Max, its first ad product spanning all Google-owned media. A year later, Performance Max exited beta. And fast-forward another year to today, and Performance Max has quietly become the fastest growing and potentially most controversial product […]

Learn everything you need to know about an ad exchange, from how they function to their impact on advertising success. Here's an A to Z guide.

by John MahoneyThis is a bucket of chum. Chum is decomposing fish matter that elicits a purely neurological brain stem response in its target consumer: larger fish, like sharks. It signals that they should let go, deploy their nictitating ...

Botmasters have created a Kafkaesque system where companies are paying huge sums to show their ads to bots. And everyone is fine with this.

Apple robbed the mob's bank, part 3. Mobile marketing and advertising, freemium monetization strategy, and marketing science. Mobile Dev Memo.

How much does Google Ads cost? Google Ads costs $100 - $10,000 per month with an average CPC of $0.11 - $0.50. Learn more about Google Ads pricing here!

Here's some common AdWords mistakes that make affect your campaigns, as well as how to fix them.

You must test ads to make your paid search account grow and thrive. That fact is no longer debatable – it is just a best practice fact. Ad testing in

A/B testing tools often lie about whether something is "statistically significant." Here's an extremely simple, mathematically sound formula to compute it for yourself.

When you do AdWords account audits, you need to go beyond the data to see how savvy the AdWords account is overall. If the account is well put together,

Finding the right mix of keywords is as much science as it is good common sense. When it comes to your brand, there are typo and URL derivation techniques

For B2B businesses in competitive markets, AdWords can be difficult to manage effectively. Columnist Todd Saunders provides some tips that will keep costs low and boost Quality Scores.

List of Advertising networks and Affiliate networks, which include CPA Networks as well as contextual and keyword targeted advertising services. Basically networks and services that provide the means for webmasters to monetize their websites. Pay per click search engines should be listed in a different category. The content network version of search engine's PPC services belong in here though.

Many sites try to avoid our ad blockers through limiting content or just straight out pleaing. Other companies are looking at encrypting any kind of indicator that screams “AD!” through obfuscation and other fancy techniques—confusing ad blockers. Here we’ll look at some interesting techniques Faceb...

Being able to get in front of trending keywords can be a valuable but difficult task. In this week's Whiteboard Friday, we'll be talking about predicting keyword volume - before the data is even in adwords!

Brave browser's policy officer questions efficacy of personalised ads

Here’s why a writer at TechCrunch called me the biggest hustler he has ever met.

Google AdWords is a good opportunity to boost sales in a short period of time for both small and large businesses alike. Learn the basics here.

We analyzed 7,000+ websites with reviews of more than 4 stars on Trustpilot. Here are some SEO factors we noticed they had in common.

Current privacy laws don’t shield people from the pervasive surveillance of Big Tech. Guerrilla tactics are all we’ve got.

Managing a Google ads campaign requires understanding how to check, optimize, test, and change your ads. Read this post to learn more.

Algorithms are meaningless without good data. The public can exploit that to demand change.

20 years ago Apple seized music, and turned it into a lever for its broader business. It failed to do the same to TV, and lost control of music, but won massively in games, where it now makes more money than the entire global digital music industry. Now, perhaps, it’s looking at advertising.

Google’s Privacy Sandbox is under increasing scrutiny throughout the digital media industry and now from the U.K. government as well.

Tests show advertisers can expect at least 95% of conversions per dollar spent on ads, compared to cookie-based advertising, Google said.

Learn the exact way that I perform keyword research that generates profitable, scalable ROI for eCommerce stores.

For the advertising industry, ad blocking is an existential crisis. For the Pi-hole community, it’s a sport.

Google’s proposals for machine learning-based frequency capping are questioned.

Authenticated consent is a term that has started to crop up more and will likely gain more steam in the future. Here's what it means.

If it feels like the ads chasing you across the internet know you a little too well, it’s because they do (unless you’re an avid user of ad blockers, i

Digital ad fraud is a volume game. Here’s a primer on how to spot the core techniques used to generate CPM fraud.

Four ways advertisers can improve transparency, control and efficiency of their programmatic buys are detailed here.

Ad tech is riddled with jargon. For those attending the digital marketing conference Dmexco in Cologne this week, here's a primer to help keep up.

Timehop's 15-person team ended up creating its own ad server. A year and a half later, CPMs have grown from $2 to $28.

Like Google and Facebook, Amazon wants to take credit for the success of ads outside its own platform.

From industry terms like "header bidding" to "AdX" to "DSPs" to internal Google terms, such as "Jedi Blue," there's a lot to wrap your head around.

Discover 10 key tactics to optimize your Google Ads campaigns, whether you run large ecommerce accounts or low-volume B2B campaigns.

The ability of the Generative Adversarial Networks (GANs) framework to learn generative models mapping from simple latent distributions to arbitrarily complex data distributions has been...

Browse 31 tasks • 61 datasets • 57

In a preprint paper, researchers at Johns Hopkins detail TrojAI, a framework for hardening AI models against adversarial attacks.

I bet most of us have seen a lot of AI-generated people faces in recent times, be it in papers or blogs. We have reached a stage where it is becoming increasingly difficult to distinguish between actual human faces and faces that are generated by Artificial Intelligence. In this post, I will help the reader to understand how they can create and build such applications on their own. I will try to keep this post as intuitive as possible for starters while not dumbing it down too much. This post is about understanding how GANs work.

A blog about Compressive Sensing, Computational Imaging, Machine Learning. Using priors to avoid the curse of dimensionality arising in Big Data.

What we'd like to find out about GANs that we don't know yet.

Nvidia's GauGAN tool has been used to create more than 500,000 images, the company announced at the SIGGRAPH 2019 conference in Los Angeles.

Emil Mikhailov is the founder of XIX.ai [http://XIX.ai] (YC W17). Roman Trusov is a researcher at XIX.ai. Recent studies by Google Brain have shown that any machine learning classifier can be tricked to give incorrect predictions, and with a little bit of skill, you can get them to give pretty much any result you want. This fact steadily becomes worrisome as more and more systems are powered by artificial intelligence — and many of them are crucial for our safe and comfortable life. Banks, sur

By openly saying, ‘This isn’t for you,’ brands signal focus and specificity. That helps the right customers feel a stronger connection.

A couple of years ago, I decided I'd had enough of ads. Not just the occasional banner or a quick pre-roll video — I mean all of them. They have to go.

New research indicates the extent to which NFL advertising dominates other forms of TV programming for marketer returns.

Booking travel online feels like shopping in an Indian bazaar: a deluge of options, no credible information, aggressive hawkers (“recommendations” and “targeted ads”), and hours of frantic search that end with purchasing something more out of exhaustion than conviction. Online travel booking is not unique in offering this miserable experience. Buying on Amazon feels like a similar sand trap. But why is that? Poor product management? A more provocative but perhaps more accurate answer is that the

Economists credit ads with two welfare‑enhancing roles: 1. Informative – trimming search costs (Stigler 1961 (pdf)). 2. Signaling – In classic models, high-quality sellers are more willing to incur large, sunk ad costs because they expect to recoup them through future sales—especially in experience-good markets where quality is learned over time (Nelson 1974). Milgrom and Roberts (1986) formalize this idea: when ad spend is costly and more valuable to better firms, it can serve as a credible

Thoughts on business models that don't seem to make perfect sense

To diversify declining revenue streams, one city metro launched a personalized ad service earlier this year, allowing individuals to purchase ad space for messages ranging from birthday greetings and job searches to marriage proposals and quirky jokes.

When it comes down to it, it’s best to think of advertising as a coordinated, decades-long campaign to annoy the heck out of you. And it works pretty well.

Dealers offer car leases for 12 months in exchange for marketing on athletes' social media accounts.

How to dig into ad libraries from Google, Meta and other platforms to track spending, narratives, campaigns and more

Originally published Feb. 17, 2022

The five types of advertising apologies, explained.

The duo 'got into deep trouble' for boarding the 'wrong train' but it turned into the ride of a lifetime for them.

I also helped undress him so he could lie down

The first installment of Digiday's two-part series on the top ad-supported streaming services provides an overview of the platforms’ offerings and an analysis of how brands and agencies distribute their ad budgets and ad placements across platforms.

In this edition of the Digiday+ Research Briefing, we examine the top ad attributes marketers want from ad-supported streaming platforms, how brands are increasing their marketing spend on YouTube, and how Walmart and Roblox are teaming up to make virtual e-commerce a reality, as seen in recent data from Digiday+ Research.

A few relevant, high-quality visuals placed next to associated text can boost users’ comprehension of your content and its memorability.

German-American artist Henry Jerome Schile was born in Oberharmersbach, Baden-Württemberg, in 1829. He emigrated to the US in 1851 and worked in New York in the middle of the 19th century. h/t: vintag.es Henry Schile’s work is described by Harry T. Peters in America on Stone as: “Though of

The NFL's television contracts account for $12.4 billion, about 43% of all sports TV deals in the U.S.

Google Ads offers seven YouTube campaign subtypes, ranging from reaching users while browsing to driving conversions.

When we talk about using different ways to share information, it's like picking the one that fits what you need! Words, pictures, and mixes of both have

A deep dive into why the DOJ thinks RGSP makes ad auctions unfair, and why Google believes it creates a better user experience.

Jeff Bezos long shunned ads. However, Amazon's juicy first-party data has enabled it to compete with Alphabet and Meta in the new digital advertising landscape.

Netflix made sonic logos — the new version of jingles — trendy. But its success is hard to replicate.

How a grainy VHS tape became one of the most famous ads of all time — and went viral before viral was even a thing.

Kroger is following in the footsteps of Giant Eagle, attempting to phase out its print inserts in newspapers and mailed to homes in favor of digital alternatives.

A comprehensive overview of the China social media landscape in 2020 - know how to navigate and help marketing teams achieve success in Chinese social!

The world's leading online dictionary: English definitions, synonyms, word origins, example sentences, word games, and more. A trusted authority for 25+ years!

Google's targeted ad initiative AdSense was initially launched as “content targeting advertising” 20 years ago this month. Here’s how it changed the internet.

How a humble bag became a humble brag

Getting started with Google Ads is a bit more complex than it used to be. This guide walks you through the initial steps of account setup.

Songs used in commercials, advertisements, events, presentations and promotional materials by Apple, Samsung, Google and Microsoft.

Lost in the Sturm und Drang of Q4 (Q for quarantine) 2020, Google introduced a beta program called Performance Max, its first ad product spanning all Google-owned media. A year later, Performance Max exited beta. And fast-forward another year to today, and Performance Max has quietly become the fastest growing and potentially most controversial product […]

Media Mix modeling, its implementation, and practical tips

Data suggests brands can blunt public awareness of species loss when they use at-risk animals in ads. Should they pay?

Inside the under-the-radar business that makes more money than Amazon Prime.

Learn everything you need to know about an ad exchange, from how they function to their impact on advertising success. Here's an A to Z guide.

by John MahoneyThis is a bucket of chum. Chum is decomposing fish matter that elicits a purely neurological brain stem response in its target consumer: larger fish, like sharks. It signals that they should let go, deploy their nictitating ...

Botmasters have created a Kafkaesque system where companies are paying huge sums to show their ads to bots. And everyone is fine with this.

How much does Google Ads cost? Google Ads costs $100 - $10,000 per month with an average CPC of $0.11 - $0.50. Learn more about Google Ads pricing here!

Let’s step away from the “hoo rah” surrounding content marketing, and discuss some legitimate strategies for creating popular, controversial content.

15 Marketing Lessons From Infomercials

I spent a lot of money on Google ads last year across Search, Display, Youtube, Discovery, and Gmail. Here's what I learned.

You must test ads to make your paid search account grow and thrive. That fact is no longer debatable – it is just a best practice fact. Ad testing in

Not sold in stores. Duhhhhhh.Neatorama is proud to bring you a guest post from Ernie Smith, the editor of Tedium, a twice-weekly newsletter that hunts for the end of the long tail. In another life, he ran ShortFormBlog.How the music industry’s TV-driven direct marketing strategies revived vintage hits, salvaged floundering careers, and brought us Zamfir’s epic pan flute.When I grew up, I listened to a lot of John Denver. Well, not really full songs, so much as the 10-second snippets of tun...

A lesson from the Australian classic rockers explains why the pop star's newest album, which hasn't generated glowing reviews or massive radio hits, still had an explosive opening sales week.

At $200 billion, the infomercial industry is twice the size of the entire TV business. How is that possible? We investigate the business model behind the Snuggie.

As consumers skip ads and streaming content balloons, brands aim to be everywhere all at once.

Saudi-backed LIV Golf shows how 'sportswashing' can backfire.

Sponsoring a football club is about more than just advertising, it's a status symbol.

Your #1 resource for digital marketing tips, trends, and strategy to help you build a successful online business.

List of Advertising networks and Affiliate networks, which include CPA Networks as well as contextual and keyword targeted advertising services. Basically networks and services that provide the means for webmasters to monetize their websites. Pay per click search engines should be listed in a different category. The content network version of search engine's PPC services belong in here though.

Your #1 resource for digital marketing tips, trends, and strategy to help you build a successful online business.

Many sites try to avoid our ad blockers through limiting content or just straight out pleaing. Other companies are looking at encrypting any kind of indicator that screams “AD!” through obfuscation and other fancy techniques—confusing ad blockers. Here we’ll look at some interesting techniques Faceb...

Roku provides the simplest way to stream entertainment to your TV. On your terms. With thousands of available channels to choose from.

Ever wondered if Google Ads are really worth it, but don't have the cash for an experiment? One's been done for you!

Tips from successful campaigns promoting everything from shapewear to prostate health.

“Money alone isn't enough to bring happiness . . . happiness when you're actually truly ok with losing everything you have.” - Tony Hsieh, Delivering Happiness: A Path to Profits, Passion, and Purpose Disclaimer: This article’s sole purpose is to address the core principles of advertising in a new and edgy  way. This is not for the faint of heart or those highly sensitive to socially charged public issues. So suck it  up and buckle up. You’re about to be taken to school (of hard knocks). Class is now in session.

TV advertising is having a good week at the upfronts, and it may be more resilient than expected. That, though, means the crash will be even more abrupt.

Brave browser's policy officer questions efficacy of personalised ads

Here’s why a writer at TechCrunch called me the biggest hustler he has ever met.

What happens when you turn off all of your Internet advertising? Apparently, nothing. This post explores how I came to the decision to turn off all ads, and what I found as a result.

I used to be very anti-advertising. Fast forward two years and several pivots, and my slightly-less-early-stage business is doing $900 per month in revenue... from ads.

All the growth in the music business now comes from old songs—with consumption of new music actually shrinking. How did we get here, and is there a way back?

Pitt. Depp. Wahlberg. Damon. Bad. Dumb. Stupid. Awful.

Current privacy laws don’t shield people from the pervasive surveillance of Big Tech. Guerrilla tactics are all we’ve got.

What Apple, Samsung, and Starbucks learned from Pepsi Photo by John Fornander on Unsplash The year was 1957, and Pepsi — like many of the youth at that time — was dealing with an ide…

The evolution of the billboard, an object that very much tends to keep pace with the times. Who doesn’t love outdoor advertising?

Algorithms are meaningless without good data. The public can exploit that to demand change.

20 years ago Apple seized music, and turned it into a lever for its broader business. It failed to do the same to TV, and lost control of music, but won massively in games, where it now makes more money than the entire global digital music industry. Now, perhaps, it’s looking at advertising.

Political parties rarely run ads to try to win over long-term loyalists. New research suggests it’s actually possible—and worthwhile.

You think they randomly choose those glaring shades of Nike, Adidas and New Balance? Think again.

Today’s films are brimming with products from big-name brands. How exactly do these partnerships work? And is the payoff worth it?

Think you got a good deal? Look again.

The goal should not be conversion but doubt.

Tests show advertisers can expect at least 95% of conversions per dollar spent on ads, compared to cookie-based advertising, Google said.

Making things look nice can take a long time, either due to lack of resources or abundance of opinions. This could delay launches, frustrate people, and waste precious energy. Those are high costs for startups or companies hoping to move fast. Is it worth it? Long ago I got fed

Publisher comment sections are not only seen has hotbeds for toxicity, but historically have been very difficult to monetize.

A schoolgirl and a former traveling Bible salesman helped turn deodorants and antiperspirants from niche toiletries into a multi-billion industry.

Finding a brand name can be a painful process but these eight rules, based on brand naming examples, cover everything to get it right.

View our video advertising glossary and learn common terms that will help you understand better the world of video advertising.

It's been 25 years since an aging prizefighter, a quirky gadget, and iconic ’90s marketing combined to take over the world.

If you make $10 profit each time you sell a product, what cost per conversion should you aim for? Answering this question isn't easy, but it can teach us a lot about how to approach advertising.

Hulu is allowing just four advertisers to run pause ads each month, which helps to explain why this new type of inventory is selling out several months in advance.

Fun Swedish stunt from McCann Stockholm creates a new rivalry

The chain's anti-preservatives pledge breaks just about every rule in advertising.

The surprising persistence of the mail-order business

For the advertising industry, ad blocking is an existential crisis. For the Pi-hole community, it’s a sport.

DTC brands credit physical stores with boosting their online sales.

Authenticated consent is a term that has started to crop up more and will likely gain more steam in the future. Here's what it means.

Ordinary Americans are using armies of phones to generate cash to buy food, diapers, and beer through ad fraud.

If it feels like the ads chasing you across the internet know you a little too well, it’s because they do (unless you’re an avid user of ad blockers, i

Consumers want to connect with a brand.

Economists explore the complex forces that shape what ends up in your shopping cart and how that might change in the online marketplace

Digital ad fraud is a volume game. Here’s a primer on how to spot the core techniques used to generate CPM fraud.

Connect with developers sharing the strategies and revenue numbers behind their companies and side projects.

Four ways advertisers can improve transparency, control and efficiency of their programmatic buys are detailed here.

Sometimes the outrageous, bizarre route is best.

How these curbside canvases came to be, according to the men who make them.

Opinion: Brands are promoting and foodies are consuming.

We ask marketers to define AI, one of the industry's most prevalent buzzwords.

The DOJ wants to show Google can do this because it has a monopoly.

Reposting my Inkhaven post on ontology of advice here.  …

Kevin Kelly co-founded Wired magazine and is the author of the book Excellent Advice for Living. We cover his concept of the Technium, why rituals are an underappreciated part of society and family life, and the importance of developing your authentic self over a lifetime.

A philosophical look at advising highlights what makes it a distinct form of interaction – and why it often goes wrong

UPDATE Several years ago on my 68th birthday I wrote up 68 bits of advice for my adult children, and posted them here. The bits were extremely popular, and they were widely shared by others. I was encouraged to write … Continue reading →

When we want people to change, we typically tell them what to do. But what if we flipped the script and asked them for their wisdom instead? Behavioral scientist Katy Milkman PhD explains the power…

Research reveals the common mistakes we make when trying to help.

Shoppers who ask AI for product recommendations bypass traditional review sites, potentially causing lost or unattributed traffic from affiliates.

Turn your passion into profit! Learn step-by-step how to start affiliate marketing as a successful side hustle.

Starting an affiliate program is one of the most effective ways to generate traction and grow your business. You authorize others to promote your

No need to create a fancy and modern website with hundreds of pages to make money online.

When it comes to making money online you’re going to have a lot of options at your disposal. Frankly, it can be quite overwhelming just choosing an online

Looking to grow your affiliate marketing site but aren't sure which affiliate network is right for you? Here's everything you need to know.

Use affinity diagramming to cluster and organize research findings or to sort design ideas in ideation workshops.

Inexperienced facilitation in affinity diagramming workshops can lead to groupings that do not serve the team goals or misrepresent underlying issues.

In marketing analytics, conjoint analysis is a technique used to gain specific insights about consumers’ preferences. Often derived from consumer surveys, conjoint analysis can tell us, for instance…

Have you ever wondered how often do you buy certain items together? Why do you buy some items together? How likely do you purchase an item…

Nailia Schwarz via Shutterstock Nautilus Members enjoy an ad-free experience. Log in or Join now . Runners can tell you that sometimes the last mile of a run seems to feel dramatically longer than the first. This perceptual distortion isn’t limited to brains addled by exercise—it’s a consistent feature of our minds.   When we […]

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In psychology, affordance is what the environment offers the individual. In design, affordance has a narrower meaning; it refers to possible actions that an actor can readily perceive.

The concept: When we look at a chair, regardless of its shape and color, we know that we can sit on it. When a fish is in water, regardless of its location, it knows that it can swim. This is known as the theory of affordance, a term coined by psychologist James J. Gibson. It…

Sarah Larson on the podcast series “Fela Kuti: Fear No Man,” a deeply reported and sonically glorious biography of the legendary Nigerian musician, Afrobeat innovator, and rebel.

A herd of elephants halfway around the world gave an adopted Dallas woman the home she always wanted.

Moniepoint’s payment machines have become ubiquitous across Nigeria. But the company faces competition from Chinese-backed OPay.

A student’s vow to overthrow one of Africa’s last ruling monarchs faces a roadblock: his own father, a soldier sworn to protect the throne.

For farmers in Senegal who struggle to read or write, sending voice notes has unlocked a new world of collaboration across the industry.

"When the wind blows you run away because you think it’s a night runner.”

Afewerki’s attack on Tigray is the culmination of the Eritrean dictator’s ambition to become master of the Horn of Africa.

Three sisters braved lions, crocodiles, poachers, raging rivers and other dangers on a 1,300-mile transnational effort to forge a new dynasty.

Nenad Georgievski writes at All About Jazz, though the world knew little about Malian music until American musicians began partnering with players from West Africa. In the 1980s, Stevie Wonder began touring with Amadou and Mariam, helping to popularize their form of Malian blues.

Western museums are under pressure to return looted treasure, but what of those in private collections?

Quick note before you jump in:

Alibaba on Monday unveiled a new artificial intelligence model Qwen 3.5 designed to execute complex tasks independently, with big improvements in performance and cost that the Chinese tech giant claims beat major U.S. rival models on several benchmarks.

Peter Steinberger is the creator of OpenClaw, an open-source AI agent framework that's the fastest-growing project in GitHub history.Thank you for listening ...

As AI agents move into production, teams are rethinking memory. Mastra’s open-source observational memory shows how stable context can outperform RAG while cutting token costs.

I just woke up Claude Code Agent Swarm on local Qwen3 Coder Next.

Goose, Block’s open-source AI coding agent, is emerging as a free alternative to Anthropic’s Claude Code, as developers weigh offline control, rate limits, and the rising cost of AI coding tools.

Anthropic’s Cowork brings Claude Code–style AI agents to the desktop, letting Claude access and manage local files and browse the web—boosting productivity while raising new security and trust risks.

New from Anthropic today is Claude Cowork, a “research preview” that they describe as “Claude Code for the rest of your work”. It’s currently available only to Max subscribers ($100 …

It’s a general-purpose AI agent. And it’s already a pretty good knowledge worker

The AI industry has a trust problem that mirrors a paradox Daniel Kahneman identified decades ago in human decision-making: people

A step-by-step practical guide on building AI agents using Gemini 3 Pro, covering tool integration, context management, and best practices for creating effective and reliable agents.

Amazon sued Perplexity this month over its Comet browser, which uses AI agents to do online shopping on your behalf. This is the first major front in the war over who gets to browse the web.

A practical guide to working with AI coding agents without the hype.

Plus prompt injection attacks against Sora 2 cameos and notes on DSPy and Litestream 0.5.0

A Coding Guide to Build an Autonomous Agentic AI for Time Series Forecasting with Darts and Hugging Face. A Step by step guide

AI agents are putting headless browsing back in the spotlight. That raises questions for publishers: How much traffic is real vs. automated?

We tested OpenAI’s ChatGPT Agent, currently only available via its $200-per-month Pro subscription.

ChatGPT agent System Card: OpenAI’s agentic model unites research, browser automation, and code tools with safeguards under the Preparedness Framework.

I taught myself how to build RAG + AI Agents in production. Been running them live for over a year now. Here are 4 steps + the only resources you really need to do the same. … Ugly truth: most “AI Engineers” shouting on social media haven’t built a single real production AI Agent or RAG system. If you want to be different - actually build and ship these systems: here’s a laser-focused roadmap from my own journey. .. 🚀 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 Because no matter how fast LLM/GenAI evolves, your ML & software foundations keep you relevant. ✅ Hands-On ML with TensorFlow & Keras: https://lnkd.in/dWrf5pbS ✅ ISLR: https://lnkd.in/djGPVVwJ ✅ Machine Learning for Beginners by Microsoft (free curriculum): https://lnkd.in/d8kZA3es … 1️⃣ 𝗠𝗮𝘀𝘁𝗲𝗿 𝗟𝗟𝗠𝘀 & 𝗚𝗲𝗻𝗔𝗜 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 → Learn to build & deploy LLMs, understand system design tradeoffs, and handle real constraints. 📚 Must-reads: ✅ Designing ML Systems – Chip Huyen: https://lnkd.in/guN-UhXA ✅ The LLM Engineering Handbook – Iusztin & Labonne: https://lnkd.in/gyA4vFXz ✅ Build a LLM (From Scratch) – Raschka: https://lnkd.in/gXNa-SPb ✅ Hands-On LLMs GitHub: https://lnkd.in/eV4qrgNW … 2️⃣ 𝗚𝗼 𝗯𝗲𝘆𝗼𝗻𝗱 𝘁𝗵𝗲 𝗵𝘆𝗽𝗲 𝗼𝗻 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 → Most demos = “if user says hello, return hello.” Actual agents? Handle memory, tools, workflows, costs. ✅ AI Agents for Beginners (GitHub): https://lnkd.in/eik2btmq ✅ GenAI Agents – build step by step: https://lnkd.in/dnhwk75V ✅ OpenAI’s guide to agents: https://lnkd.in/guRfXsFK ✅ Anthropic’s Building Effective Agents: https://lnkd.in/gRWKANS4 … 3️⃣ 𝗥𝗔𝗚 𝗶𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕 Real Retrieval-Augmented Generation requires: → Chunking, hybrid BM25 + vectors, reranking → Query routing & fallback → Evaluating retrieval quality, not just LLM output ✅ RAG Techniques repo: https://lnkd.in/dD4S8Cq2 ✅ Advanced RAG: https://lnkd.in/g2ZHwZ3w ✅ Cost-efficient retrieval with Postgres/OpenSearch/Qdrant ✅ Monitoring with Langfuse / Comet … 4️⃣ 𝗚𝗲𝘁 𝘀𝗲𝗿𝗶𝗼𝘂𝘀 𝗼𝗻 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 & 𝗜𝗻𝗳𝗿𝗮 → FastAPI, async Python, Pydantic → Docker, CI/CD, blue-green deploys → ETL orchestration (Airflow, Step Functions) → Logs + metrics (CloudWatch, Prometheus) ✅ Move to production: https://lnkd.in/dnnkrJbE ✅ Made with ML (full ML+infra): https://lnkd.in/e-XQwXqS ✅ AWS GenAI path: https://lnkd.in/dmhR3uPc … 5️⃣ 𝗪𝗵𝗲𝗿𝗲 𝗱𝗼 𝗜 𝗹𝗲𝗮𝗿𝗻 𝗳𝗿𝗼𝗺? → Stanford CS336 / CS236 / CS229 (Google it) → MIT 6.S191, Karpathy’s Zero to Hero: https://lnkd.in/dT7vqqQ5 → Google Kaggle GenAI sprint: https://lnkd.in/ga5X7tVJ → NVIDIA’s end-to-end LLM stack: https://lnkd.in/gCtDnhni → DeepLearning.AI’s short courses: https://lnkd.in/gAYmJqS6 … 💥 𝗞𝗲𝗲𝗽 𝗶𝘁 𝗿𝗲𝗮𝗹: Don’t fall for “built in 5 min, dead in 10 min” demos. In prod, it’s about latency, cost, maintainability, guardrails. ♻️ Let's repost to help more people on this journey 💚

Learn how to build your own agentic AI application with free tutorials, guides, courses, projects, example code, research papers, and more.

TL;DR: I developed a simple, open-source benchmark to test if LLM agents follow high-level safety principles when they conflict with a given task acc…

Discover how Anthropic approaches the development of reliable AI agents. Learn about our research on agent capabilities, safety considerations, and technical framework for building trustworthy AI.

Design, test, and deploy multi-agent systems in hours using the powerful agentic frameworks.

Confused by AI agent frameworks? This article makes sense of A2A and MCP.

“It’s not that hard to build a fully functioning, code-editing agent.” Thorsten Ball

A blog post covering tips and tricks that have proven effective for using Claude Code across various codebases, languages, and environments.

Building a fully functional, code-editing agent in less than 400 lines.

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Q-learning is a model-free reinforcement learning algorithm that enables agents to learn optimal actions through interaction with their environment.

Check out this comparison of 5 AI frameworks to determine which you should choose.

In our previous tutorial, we built an AI agent capable of answering queries by surfing the web. However, when building agents for longer-running tasks, two critical concepts come into play: persistence and streaming. Persistence allows you to save the state of an agent at any given point, enabling you to resume from that state in future interactions. This is crucial for long-running applications. On the other hand, streaming lets you emit real-time signals about what the agent is doing at any moment, providing transparency and control over its actions. In this tutorial, we’ll enhance our agent by adding these powerful

Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.”

Building on Aggregation Theory, this provides a precise definition of the characteristics of aggregators, and a classification system based on suppliers. Plus, how to think about aggregator regulat…

The disruption caused by the Internet in industry after industry has a common theoretical basis described by Aggregation Theory.

Airbnb gets less press than Uber, but in some respects its even more radical: understanding how it works leads one to question many of the premises of modern society from hotels to regulations. It&…

Because of the Internet realities described by Aggregation Theory a smaller number of companies hold an increasing amount of power. However, an increasing focus on market forces reduces the latitud…

It is all but impossible to beat an Aggregator head-on, as Walmart is trying to do with Amazon. The solution instead is to build a platform like Shopify.

Aggregators, by virtue of owning demand, gain power over suppliers which become modularized and commoditized. The Moat Map The Moat Map describes the correlation between the degree of supplier diff…

Aggregation Theory provides a framework to understand the impact of the Internet on nearly all industries.

It’s time to bring together recent breakthroughs in AI to help solve information overload when you need quality recommendations the most.

The Moat Map describes the correlation between the degree of supplier differentiation and the externalization (or internalization) of a company’s network effect.

Sprints promise to accelerate development, but often do the opposite. Check out this alternative approach to building software.

Richard Speed reports via The Register: A study has found that software projects adopting Agile practices are 268 percent more likely to fail than those that do not. Even though the research commissioned by consultancy Engprax could be seen as a thinly veiled plug for Impact Engineering methodology...

Planning poker, also called Scrum poker, is a consensus-based, gamified technique for estimating, mostly used for timeboxing in Agile principles. In planning poker, members of the group make estimates by playing numbered cards face-down to the table, instead of speaking them aloud. The cards are revealed, and the estimates are then discussed. By hiding the figures in this way, the group can avoid the cognitive bias of anchoring, where the first number spoken aloud sets a precedent for subsequent estimates.

Unsure of what a word means and how it applies to UX in-practice? Use this glossary to quickly clarify key terms and Agile concepts.

Introduction: The software development process has been transformed by the DevOps...

Agile is made up of 12 guiding principles that serve as the foundation for project teams. These...

The scaled agile framework (SAFe) is a set of organization and workflow patterns intended to guide enterprises in scaling lean and agile practices.[1][2] Along with disciplined agile delivery (DAD) and S@S (Scrum@Scale), SAFe is one of a growing number of frameworks that seek to address the problems encountered when scaling beyond a single team.[3][4]

Principles built into Lean UX don’t exist in SAFe. Continuous learning and improvement, customer centricity, humility, cross-functional collaboration and more.

Run effective SAFe ceremonies with these tips for release train engineers.

Make the best choice for your Agile team with this scaling framework overview.

Agile methodologies theory, practice, examples, and free templates for product development and product management teams.

A way to communicate, quantify, validate, and design for a Job to be Done

USDA research points to viruses spread by pesticide-resistant mites, indicating a worrying trend

A fast-spreading bacteria could cause an olive-oil apocalypse.

Wherever you find an old homestead—a house and barn with a little bit of land that has stood from sometime in the 1800s or early 1900s—you’ll find an

Ethanol is a comically inefficient form of solar energy—and a toxic one. Putting regular solar panels on some of that land would be better.

In 1970s Bali, a sudden rice crisis prompted an unexpectedly far-reaching scientific discovery

A tiny town in Wisconsin faces a lawsuit from an industry heavyweight, a growing trend when citizens try to regulate CAFOs in their backyards.

Master falconer Alina Blankenship and her mélange of raptors have become the protectors of some of Oregon's top vineyards.

The area devoted to growing the three top crops is bigger than the size of Texas. But even on that podium there’s only one king.

Vidalia Onions to be exact. They’re classified as a sweet onion, and because of their mild flavor (they don’t make your eyes tear up), some folks can eat them like an apple. Most of my customers do. During a phone order one season – 2018 I believe – a customer shared this story where he ... Read more

Capitalism, corruption and exploitation created the broken system of ‘insurance farming’—and the biggest loser is the American taxpayer.

Cody Easterday wagered hundreds of millions of dollars on the price of beef. He lost.

Growers of New Mexico’s iconic crop wrestle with drought, water rights and labor shortages.

Why it’s getting harder to stop multinational corporations.

Cropster started as a tool to lift coffee producers out of poverty. Now it has a bigger mission: to save the entire global food supply.

One method, the slow, methodical work of traditional hybridization, is long familiar. The other, genetic engineering, is more controversial.

Farmers like sixth-generation Illinois farmer Ethan Cox can't wait for policymakers to protect them from climate change. To survive, they have to adapt their operations now, if they can.

In an isolated Northern California community, the last remnants of the counterculture are confronting the future of cannabis.

Almond growing in California is a $7.6 billion industry that wouldn’t be possible without the 30 billion bees (and hundreds of human beekeepers) who keep the trees pollinated — and whose very existence is in peril.

Platform created by the community to programmatically author, schedule and monitor workflows.

Lesser known Tips, Tricks, and Best Practises to use Apache Airflow and develop DAGs like a Pro

Lessons learned from successful MLOps implementation

Chapter 5 excerpt of “Data Science in Production”

A firsthand look at winter camping in Quartzsite, Arizona—where nomads find affordable meals, unexpected community, and a place to belong.

From full time engineers on the road, a discussion of the good, the bad, and the ugly of if Starlink is good for Van Life: Gen 2, Gen 3, & Flat Mounted, High Performance.

Call 1-800-755-4775 to schedule an appointment for a free appraisal of your RV. This will allow PPL to find a qualified buyer for your RV

Auto, Truck, and RV repair services in our South Charleston WV Repair Shop. List of services at VMS.

Built on a 148” AWD Ford Transit, this nautical-inspired van conversion is loaded with high-end components and fun and functional design elements. With seating and sleeping for four, a full interior kitchen galley with an exterior stove, ample storage space, and tons of exterior metalwork, this rig is ready to hit the road!

Get a van for sale that suits your need here at the CASCADE VAN BEND, OR website. Click for more information about us today.

Airstream Rangeline features a modern, European-inspired interior that puts a premium on flexible functionality and off-grid capability.

Beachside RV parks are hotspots for sun, sea, and fun! Explore vibrant coastal communities, splash in the waves, and get away from it all.

The most advanced light weight travel trailer in the world. Built with honest materials for a lifetime of adventures.

Architects, designers, and DIYers revamp the classic travel trailers to serve as contemporary workspaces, rentals, and even primary residences.

Get free shipping on qualified 15/16 in Sockets products or Buy Online Pick Up in Store today in the Tools Department.

Motor Starting Marine/RV Battery The GPL-2400T is a high performance, Mil-Spec, AGM battery, produced in the United States. Due to the Lifeline Battery's quality construction, it has an industry leading 2% per month self discharge rate at 77°F (25°C), compared to 10%+ for conventional batteries. Coast Guard approved, DOT Haz Mat Exempt, and longer lifespans than conventional batteries. Warrantied installations include marine, yacht, and other seafaring applications.

Drive Reach is our most powerful, in-vehicle cell signal booster yet. It can reach the farthest cell towers in remote areas. Learn more here!

Learn more about the expected lifepsan of AGM batteries from Lifeline Batteries.

RVs are large and complex vehicles that require a lot of upkeep. There are a few RV repairs that the average person can easily fix.

Welcome to Ofland (formerly Yonder)! We've changed our name! New Name. Same Magic. More Adventure. Learn More here.

Across US public lands thousands of people are taking to van life, as featured in the Oscar-winning film Nomadland

The Flying Cloud 30FB Office was designed with productivity and connectivity in mind.

I thought I’d start a post that catalogs “events of significance” in my ownership of a 2019 Airstream Globetrotter 27FBT (named after my maternal grandfather, who we called “Tat

Big-box parking lots are an easy stopgap, but there’s so much public land waiting for those willing to look a little.

Camping equipment for the savvy off roader, overland traveler Camping grills, lantern hangers, 12 volt fridge slides and overland travel equipment.

The iconic brand is digging deep to provide local intel and gear marketed to a younger fan base.

Some begin high and end low, others boldly swoop into half circles and curves; but somehow, on RVs big and small, decorative swoops are the go-to design element of choice.

The new Eriba Touring 820 is an example of what a 21st-century trailer can look like when manufacturers forego the clichéd design tropes of the past.

About a million Americans live full-time in RVs. Many say this modern nomadic lifestyle has improved their marriages and made them much happier.

A mess of cheap wood laminate, outdated fabrics, and torn up floors transforms into an airy dream home on wheels.

New Airstreams have all the bells and whistles customary in pricey builds, but nothing beats the vintage style of an old Airstream, made modern.

An olive paint job and Victorian card table for a 1968 Airstream Overlander? That was the approach taken by San Miguel-based Mex-chic design house Casamidy.

A hands-on introduction to elliptic curve cryptography. Start with curve geometry, build point addition and scalar multiplication, see why ECDLP is hard, and then use that math in ECDH, ECDSA, and ECIES.

A Laplace transform is a type of integral transform that acts on functions.

ANN — Approximate Nearest Neighbors —  is at the core of fast vector search, itself central to GenAI, especially GPT and LLM. My new methodology, abbreviated as PANN, has many other app…

Swarm Intelligence (SI) represents a significant paradigm within artificial intelligence, drawing inspiration from the collective behaviors of natural systems to solve complex computational problems. However, the conventional classification of SI algorithms often groups them monolithically or based on superficial characteristics like the inspiring organism, obscuring crucial differences in their underlying operational mechanisms. This article addresses this limitation by proposing a novel taxono

How a privacy researcher proved a politician wrong, and how she created the first ever definition of anonymity in the process.

Hotels and landlords can mitigate legal risks by choosing decentralized revenue management systems that use public data.

True drone swarms can cut costs and boost efficiency in agriculture, logistics and humanitarian demining, but software remains a hurdle.

Dithering is still a surprisingly applicable technique, not just for practical reasons (such as preparing a full-color image for output on a non-color printer), but for artistic reasons as well. Dithering also has applications in web design, where it is a useful technique for reducing images with high color counts to lower color counts, reducing file size (and bandwidth) without harming quality. It also has uses when reducing 48 or 64bpp RAW-format digital photos to 24bpp RGB for editing.

Recent findings reveal that even simple pricing algorithms can make things more expensive.

Multisets are sets that allow repetition of elements. As such, multisets pave the way to a number of interesting possibilities of theoretical and applied nature. In the present work, after revising the main aspects of traditional sets, we introduce some of the main concepts and characteristics of multisets, followed by their generalization to take into account vectors and matrices. An approach is also proposed in which the real, negative multiplicities are allowed, implying the multiset universe to become finite and well-defined, corresponding to the multiset with null multiplicities. The complement operation in multisets is then defined, which allows properties involving complement -- including the De Morgan theorem -- to be recovered in multisets. In addition, it becomes possible to extend multisets to functions (which become multifunctions), scalar fields and other continuous mathematical structure, therefore achieving an enhanced space endowed with all algebraic operations plus set theoretical operations including union, intersection, and complementation. The possibility to define a set operation between mfunctions, namely the common product, that is analogous to the traditional inner product is also proposed, paving the way to obtaining respective mfunction transformations, and it is argued that the Walsh functions provide an orthogonal basis for the mfunctions space under the common product. This result also allowed the proposal of performing integrated signal processing operations on mset mfunctions, including filtering and enhanced template matching. Relationships between the cosine similarity index and the Jaccard index are also identified, including the presentation of an intersection-based variation of the cosine index. The potential of multisets in pattern recognition and deep learning is also briefly characterized and illustrated.

Introduction to the BLS12-381 curve used in Ethereum's consensus layer. Focus on concrete calculations to make the curve more tangible.

Generating random points inside a sphere of any dimension.

Our physics expert picks his top-five equations, plus a scheme to supply US power needs with a bucket of baseballs. Thanks, Einstein!

These five equations should be part of your mental toolkit. They might even improve your bowling score.

When the streaming giant began making films guided by data that aimed to please a vast audience, the results were often generic, forgettable, artless affairs. But is there a happy ending?

This article explains how these four things fit together and shows some examples of what they are used for. Derivatives Derivatives are the most fundamental concept in calculus. If you have a funct…

Raft is a consensus algorithm that is designed to be easy to understand.

Find out how this simple algorithm from the 1960s keeps your wallet safe

After just a few months of work, a complete newcomer to the world of sphere packing has solved one of its biggest open problems.

Google Android’s calculator is (probably) the most widely used calculator in the world. It’s also the most advanced.

The most important factor left out of the two body problem is the J2 effect, due to the fact that the earth is not a sphere of uniform density.

Guest Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Quantum computing (QC) brings with it a mix of groundbreaking possibilities and significant risks. Major tech players like IBM, Google, Microsoft and Amazon have already rolled out commercial QC cloud services, while […]

Merkle Trees in the real world

A visual, interactive guide to what bloom filters are, when you would use them, and how they work.

Ruby implementation of Algorithms,Data-structures and programming challenges - kumar91gopi/Algorithms-and-Data-Structures-in-Ruby

Evolutionary algorithms are optimization techniques inspired by natural evolution, solving complex problems through processes like selection, adaptation, and mutation.

In 1993, Intel released the high-performance Pentium processor, the start of the long-running Pentium line. I've been examining the Pentium'...

"A calculator app? Anyone could make that." (this was originally a https://x.com/ChadNauseam/status/1890889465322786878) Not true. A calculator should show you the result of the mathematical expressi…

A young computer scientist and two colleagues show that searches within data structures called hash tables can be much faster than previously deemed possible.

How a Key-Value (KV) cache reduces Transformer inference time by trading memory for computation

To celebrate Rafael Araujo's talent and vision, I have curated a selection of his most stunning illustrations, showcasing the elegance and intricacy of his work.

Cosine similarity - the duct tape of AI. Convenient but often misused. Let's find out how to use it better.

Intel released the powerful Pentium processor in 1993, establishing a long-running brand of high-performance processors. 1 The Pentium incl...

Dramatically Speed-Up your Learning Algorithm, with Stochastic Thinning. Includes use case, Python code, regression and neural network illustrations.

BM25 is a widely used algorithm for full text search. I wanted to understand how it works, so here is my attempt at understanding by re-explaining.

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are particularly effective when dealing with complex datasets. The core principle behind SVM is to identify the optimal hyperplane that effectively separates data points into different classes while maximizing the margin between them. SVMs have gained significant popularity due to their ability to handle both linear and non-linear classification problems. By employing kernel functions, SVMs can map data into higher-dimensional feature spaces, capturing intricate patterns and relationships that may not be apparent in the

A pseudorandom number generator may have good statistical properties but be insecure. But a physical RNG with good statistical properties is probably secure.

When their pay suddenly dropped, delivery drivers audited their employer

How phrase search works in search array by intersecting roaring-like numpy arrays.

All that lexical search context you need to build that RAG app

Understanding what genetic algorithms are and how they can be implemented in Python.

By Christos Kasparis, EnSilica EETimes (May 15, 2024)   The rise of quanum computing paints a significant challenge for the cryptography we rely on today. The modern encryption standards we currently use to safeguard sensitive data and communications, such as DSA, public key RSA and those based on elliptic curves, will eventually be broken by

papad Hard to believe Sanjeev Arora and his coauthors consider it “a basic tool [that should be] taught to all algorithms students together with divide-and-conquer, dynamic programming, and random sampling.” Christos Papadimitriou calls it “so hard to believe that it has been discovered five times and forgotten.” It has formed the basis of algorithms in machine learning, optimization, game theory, economics, biology, and more. What mystical algorithm has such broad applications?

Current encryption methods will likely be broken by 2030. Embedded systems in development now will have a reasonable chance of encountering attacks.

an open source textbook and reference work on algebraic geometry

we help students master the Kalman Filter

More and more industries are adopting “dynamic pricing” — and consumers aren’t happy.

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape.

1. Preface Garbage Collection (GC) is an important feature of automatic memory management...

A Schur decomposition of a matrix $latex A\in\mathbb{C}^{n\times n}$ is a factorization $LATEX A = QTQ^*$, where $LATEX Q$ is unitary and $LATEX T$ is upper triangular. The diagonal entries of $LAT…

Tired of equations and matrices? Ready to learn the easy way? This post explains the Kalman Filter simply with pictures and examples!

Many Data Scientists overuse ML and neglect Mathematical Optimisation, even though it’s great for your career and easy to learn

Insanely fast and reliable smoothing and interpolation with the Whittaker-Eilers method.

In this article, I'll take you through the task of Market Basket Analysis using Python. Market Basket Analysis using Python.

Notebooks for the python tutorials of my youtube channel. See specific youtube video for link to specifc notebook. - lukepolson/youtube_channel

Definitions of algorithms, data structures, and classical Computer Science problems. Some entries have links to implementations and more information.

Research shows knowledge graphs and graph embeddings improve the quality and accuracy of Gen AI responses. Here’s how to get started.

Open Source resource for learning Data Structures & Algorithms and their implementation in any Programming Language

Read my manifesto on Code as an alternative to Mathematics. Code for this article can be found on this Colab Notebook should you choose to follow along. Why Kalman Filters? Kalman filters are ingenius. If you have never heard of them, then a very intuitive (and arguably reductive) way to think about them is to

A case study with step-by-step code implementation

Hierarchical Navigable Small World (HNSW) is a state-of-the-art algorithm used for an approximate search of nearest neighbours. Under the…

In the first two parts of this series we have discussed two fundamental algorithms in information retrieval: inverted file index and…

Hierarchical Navigable Small World graphs (HNSW) is an algorithm that allows for efficient nearest neighbor search, and the Sentence…

Similarity search is a popular problem where given a query Q we need to find the most similar documents to it among all the documents D.

Learn a powerful technique to effectively compress large data

Explore how similarity information can be incorporated into hash function

Understand how to hash data and reflect its similarity by constructing random hyperplanes

Dive into combinations of LSH functions to guarantee a more reliable search

Introduction: In the quest to solve complex optimization problems and simulate natural evolution,...

In this article we will learn about its definition, differences and how to calculate FLOPs and MACs using Python packages.

All of the formulas

A simple geometric idea has been used to power advances in information theory, cryptography and even blockchain technology.

Concise summary of the Hilbert transform: mathematics, effects on signals, and applications in telecommunications.

Circular functions and hyperbolic functions are special cases of the Jacobi functions. This post shows how.

Breaking down one of the less well-known distributions in data science

Working code examples meant to clarify AlphaDev's deep learning assembly optimizations.

Andrew Wiles thought he had a solution to an age-old puzzle. Until it began to unravel.

Understanding the most underrated trick in applied Machine Learning

Telfar has introduced a “Live Price” pricing model based on customer demand.

Why do we use the logistic and softmax functions? Thermal physics may have an answer.

How bid density impacts ads, recommender systems, and salary negotiations.

A researcher has solved a nearly 60-year-old game theory dilemma called the wall pursuit game, with implications for better reasoning about autonomous systems such as driver-less vehicles.

I really enjoyed reading Algorithmic Trading: A Practitioner’s Guide by Jeffrey M. Bacidore. Before starting, I imagined it would cover various strategies for trading in the markets, along th…

While world record holders may have memorized more than 70,000 digits of pi, a JPL engineer explains why you really only need a tiny fraction of that for most calculations – even at NASA.

List of parsing algorithms

Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural networks that uses two forward passes of data through the network, instead of backpropagation, to update the model weights.

Delve deeper into the concept of multi-armed bandits, reinforcement learning, and exploration vs. exploitation dilemma.

Graph-based models capture correlations efficiently enough to enable machine learning at scale.

This is the Fourier Transform. You can thank it for providing the music you stream every day, squeezing down the images you see on the Internet into tiny

Let's say you want to send an encrypted message to your friend in order to avoid it being intercepted...

NIST has formally retired the widely used 27-year-old SHA-1 cryptographic algorithm, bringing cryptographic security into the modern age.

3rd edition

How to Choose the Best Machine Learning Technique: Comparison Table

What is a wave function and why does it collapse? Wave function collapse is a algorithm...

When quantum computers become powerful enough, they could theoretically crack the encryption algorithms that keep us safe. The race is on to find new ones.

The guide provides a practical introduction to Digital Signal Processing, covering a wide range of topics. It is an ideal introduction for those new to DSP, and an excellent reference for more experie

A comparison between different topic modeling strategies including practical Python examples

We have curated almost thirty suggested math books by Neil Sainsbury for self-learners. All those books help you in different fields of math.

From a theoretical introduction to the hands-on implementation: here’s what you need to know about the Chirplet Transform

Finding the adjacency graphs for US states and Texas counties using Mathematica

A detailed primer on Roaring bitmaps explaining what they are, how they're different from traditional bitmaps, and how they work internally.

The Cyber Swiss Army Knife - a web app for encryption, encoding, compression and data analysis

Left unchecked, pricing algorithms might unintentionally discriminate and collude to fix prices

As of 2024, The Data Incubator is now Pragmatic Data! Explore Pragmatic Institute’s new offerings, learn about team training opportunities, and more.

In this article, we discuss the importance of linear algebra in data science and machine learning.

Brain-inspired unsupervised machine learning through competition, cooperation and adaptation

Quantifying Uncertainty in Computation.

Articles, software, calculators, and opinions.

No need to worry about getting stuck in local minima anymore

Illustrated study guides ideal for visual learners.

Personalization algorithms influence what you’ve chosen yesterday, what you choose today and what you’ll be choosing tomorrow. Simultaneously, there seems to be something wrong with personalization. We are continuously bumping into obtrusive, uninteresting ads. Our digital personal assistant isn’t that personal at all. We’ve lost friends to the algorithmic abyss of the News feed. The content we encounter online seems to repeat the same things again and again.

More and more companies are announcing new products based on human curation, even as the most important content players — Google and Facebook — rely on algorithms. When does curation make sense, an…

Six matrix factorizations dominate in numerical linear algebra and matrix analysis: for most purposes one of them is sufficient for the task at hand. We summarize them here. For each factorization …

The Shazam music recognition application made it finally possible to put a name to that song on the radio. But how does this magical miracle actually work? In this article, Toptal Freelance Software Engineer Jovan Jovanovic sheds light on the principles of audio signal processing, fingerprinting, and recognition,...

Here at Trail of Bits we review a lot of code. From major open source projects to exciting new proprietary software, we’ve seen it all. But one common denominator in all of these systems is that fo…

Machine learning is a subfield of artificial intelligence (AI) and computer science that focuses on using data and algorithms to mimic the way people learn, progressively improving its accuracy. This way, Machine Learning is one of the most interesting methods in Computer Science these days, and it'

Because Graph Analytics is the future

A detailed explanation of Bézier curves, and how to do the many things that we commonly want to do with them.

There are many great boosting Python libraries for data scientists to reap the benefits of. In this article, the author discusses LightGBM benefits and how they are specific to your data science job.

📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings - trekhleb/javascript-algorithms

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. - eugeneyan/applied-ml

Quantum Lab: Scientists are fabricating quantum photonic circuits—consisting of waveguides and other elements—to manipulate single photons for future quantum communications and processing.Oak Ridge National Laboratory / Flickr Nautilus Members enjoy an ad-free experience. Log in or Join now . Justin Trudeau, the Canadian prime minister, certainly raised the profile of quantum computing a few notches […]

Efficient matrix multiplication · GitHub

An essay that bids farewell to x87 – a computing architecture too long for this world.

What We Talk about When We Talk about Performance.

Interactive article explaining how curves and surfaces are modeled.

All Algorithms implemented in Python.

An introduction to the Kalman and Particle Filters and their applications in fields such as Robotics and Reinforcement Learning.

Compendium of free ML reading resources.

Multiplying matrices is among the most fundamental and compute-intensive operations in machine learning. Consequently, there has been significant work on efficiently approximating matrix...

The ten essential computer vision terminologies that everyone should learn to become more proficient at computer vision with sample codes

An in-depth guide to understanding node2vec algorithm and its hyper-parameters

What would a totally new search engine architecture look like? Who better than Julien Lemoine, Co-founder & CTO of Algolia, to describe what the future of search will look like. This is the first article in a series. Search engines, and more generally, information retrieval systems, play a central role in

This is part 3 of a series on bot programming originally published on the Coder One blog. Part 1:...

How does a generator in Python work?

Explanation and examples of frequent itemset mining and association rule learning over relational databases in Python

Technique used to gain insights about consumers’ preferences

Poisson's Equation is an incredibly powerful tool...

Different Kinds of Correlation Coefficients in a Deeper Look

What companies can learn from employee turnover data

All Algorithms implemented in Python.

A Not Boring x Jill Carlson Collab on Moon Math, Privacy, and Hype

Reconstructing Images using Reinforcement Learning and Genetic Algorithms

In this edition of the Algorithm Tutorial series, we're going to break down the Heap data structure...

Learn how mathematics influence every aspect of our life.

It’s even more astonishing than Dan Brown and Pepsi thought.

This is the first in a series of articles about Information Theory and its relationship to data driven enterprises and strategy. While…

"One person's data is another person's noise." ― K.C. Cole - manjunath5496/Data-Technology-Books

In this story, we are going to discuss an application of dynamic programming techniques to an optimization algorithm. Through the process of developing an optimal solution, we get to study a variety…

A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements.

What you need to know as graph theory adoption continues to take off

Weighted Shortest Job First (WSJF) is a prioritization model used to sequence work for maximum economic benefit. In SAFe, WSJF is estimated as the relative cost of delay divided by the relative job duration.

Demystifying the inner workings of BFGS optimization

For statistics and control theory, Kalman filtering, also known as linear quadratic estimation, is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is constructed as a mean squared error minimiser, but an alternative derivation of the filter is also provided showing how the filter relates to maximum likelihood statistics. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory.

Instacart crunches petabytes daily to predict what will be on grocery shelves and even how long it will take to find parking

The Huffman Coding algorithm is a building block of many compression algorithms, such as DEFLATE - which is used by the PNG image format and GZIP.

Neural Cellular Automata learn to generate textures, exhibiting surprising properties.

This is a collection of introductory, expository notes on applied category theory, inspired by the 2018 Applied Category Theory Workshop, and in these notes we take a leisurely stroll through two...

By making the first progress on the “chromatic number of the plane” problem in over 60 years, an anti-aging pundit has achieved mathematical immortality.

A Single-Pass Learned Index.

Master these data structures to land in your next data science job

This website is for sale! benchmarkfcns.xyz is your first and best source for all of the information you’re looking for. From general topics to more of what you would expect to find here, benchmarkfcns.xyz has it all. We hope you find what you are searching for!

This is the next installment in the "Practical Computer Science" series, where you will learn how to apply classic computer science concepts to solve real problems using Ruby. Today we are going to talk about Graph

The string matching problem also known as “the needle in a haystack” is one of the classics. This simple problem has a lot of application…

Demystifying the inner workings of BFGS optimization

In this story, we’re going to take an aerial tour of optimization with Lagrange multipliers. When do we need them? Whenever we have an…

Learn PSO algorithm as a bedtime story with GIFs and python code

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape.

Understand how the Discrete Cosine Transform or DCT works and is used in Image and Video compression to reduce the size of the data without affecting quality.

The Navier-Stokes equations describe simple, everyday phenomena, like water flowing from a garden hose, yet they provide a million-dollar mathematical challenge.

Peregrine: A Pattern-Aware Graph Mining System.

Multi-Armed Bandits: Part 6

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

Understand the basic functions required for computing time complexity

To Infinity and…Linear Algebra?!

Intuitive explanations for the Normal, Bernoulli, Binomial, Poisson, Exponential, Gamma and Weibull distribution — with Python example code

Floating-point formats are not the most glamorous or (frankly) the important consideration when working with deep learning models: if your model isn’t working well, then your floating-point format certainly isn’t going to save you! However, past a certain point of model complexity/model size/training time, your choice of floating-point format can have a significant impact on your model training times and even performance. Here’s how the rest of this post is structured:

Data Structures & Algorithms (DSA) is often considered to be an intimidating topic - a common...

Science News, Physics, Science, Philosophy, Philosophy of Science

Understanding why it works

A complete guide on the famous Euler's formula for complex numbers, along with its interpretations, examples, derivations and numerous applications.

Optimization by natural selection

Get the Book on Evolutionary Algorithms (With Python Notebooks) https://datacrayon.com/shop/product/practical-evolutionary-algorithms-book/ 3:06 - To skip to the main content Twitter: @ShahinRostami (http://twitter.com/ShahinRostami) An introduction to the topic of Evolutionary Computation, with a simple example of an Evolutionary Algorithm. This introduction is intended for everyone, specially those who are interested in learning about something new. No pre-existing knowledge of the subject or any scientific background is expected. More educational content: https://shahinrostami.com Slides: https://www.researchgate.net/publication/310365190_Introduction_to_Evolutionary_Algorithms Further playing: http://rednuht.org/genetic_cars_2/ http://boxcar2d.com Related Topics: optimisation, machine learning, neural network

A deep-dive into the theory and application behind this Machine Learning algorithm in Python, by a student

One of the most powerful & useful coding approaches

Do you actually use data structures and algorithms on your day to day job? I've noticed a growing trend of people assuming algorithms are pointless questions that are asked by tech companies purely as an arbitrary measure. I hear more people complain about how all of this is a purely

Mathematical Background and Example

We show how to emulate Brownian motion, the most famous stochastic process used in a wide range of applications, using simple Python code.

This course focuses on the algorithms for analyzing and designing geometric foldings. Topics include reconfiguration of foldable structures, linkages made from one-dimensional rods connected by hinges, folding two-dimensional paper (origami), and unfolding and folding three-dimensional polyhedra. Applications to architecture, robotics, manufacturing, and biology are also covered in this course. Acknowledgments --------------- Thanks to videographers Martin Demaine and Jayson Lynch.

How to safely reopen offices, schools and other public spaces while keeping people six feet apart comes down to a question mathematicians have been studying for centuries.

Adam Kucharski wrote The Rules of Contagion before Covid-19. He talks about misinformation, bank failures, and coming up with hypotheses during a crisis.

It doesn’t quite get the audiophile seal of approval, but scientists are very intrigued.

Understanding the beauty of calculus

Understand the Ultimate Linear Algebra concept with Geometry

Genetic Algorithm (or Evolutionary Algorithm) — A simple, yet very powerful optimization technique which has seen resurgence in popularity…

This Frequent Engineering Question gives a quick overview of an important mathematical technique used in digital signal processing, calculating the z-transform.

In this series of articles, discover how genetic algorithms (also called evolutionary algorithms) can help you solve non-linear problems!

There are two types of engineers, the ones that can quickly do estimates and the ones that can’t. Are these people just smarter, or is there more to it? Enrico Fermi was a master at estimation Back of the envelope estimation is a skill that can be learned with practice. It becomes easier once you get familiar with some tricks of the trade. Know your numbers How fast can you read data from the disk?

Bayesian Approach to Machine Learning

Applied to the optimization of a meal plan for macronutrients

Often, the input features for a predictive modeling task interact in unexpected and often nonlinear ways. These interactions can be identified and modeled by a learning algorithm. Another approach is to engineer new features that expose these interactions and see if they improve model performance. Additionally, transforms like raising input variables to a power can help to better expose the…

New method reduces training time by up to 99%, with no loss in accuracy.

How does it actually work?

An elegant method to group predictions without labeling

Using q-learning for sequential decision making and therefore learning to play a simple game.

Pandas is the go-to library for data science. These are the shortcuts I use to do repetitive data science tasks faster and simpler.

A tank level measurement application to help you develop intuition on Kalman Filters

How n-body problems are solved in linear time, without any maths.

An algorithm for community finding

Learn matrix multiplication for machine learning by following along with Python examples

Finding relationships between different variables/ features in a dataset during a data analysis task is one of the key and fundemental…

A comprehensive but simple guide which focus more on the idea behind the formula rather than the math itself — start building the block…

It’s not a silver bullet metric to classification problems

An intuitive explanation of t-SNE algorithm and why it’s so useful in practice.

An Explanation and Implementation of Matrix Factorization

The Bloom filter provides fast approximate set membership while using little memory. Engineers often use these filters to avoid slow operations such as disk or network accesses. As an alternative, a cuckoo filter may need less space than a Bloom filter ...

Networks regulate everything from ant colonies and middle schools to epidemics and the internet. Here’s how they work.

How to reduce storage size without losing information.

[bibshow file=own_pub.bib] DEPSO [bibcite key=Zhang:2003p3816], or called DEPS, is an algorithm for (constrained) numerical optimization problem (NOP). DEPSO combines the advantages of Particle Swarm Optimization (PSO) and Differential Evolution (DE). It is incorporated into cooperative group optimi

Since deep neural networks were developed, they have made huge contributions to everyday lives. Machine learning provides more rational advice than humans are capable of in almost every aspect of...

A practical introduction on how to program Evolutionary Algorithms in Python to solve optimization tasks.

A litany of issues in business, finance, container ship loading and aircraft loading derive from this one simple dilemma

Intro If you're into Cryptography For Beginners, you're in the right place. Maybe you're j...

The Dormand-Prince algorithm is similar to the popular RKF45 adaptive Runge-Kutta method but produces more precision relative to the amount of computation.

PRML algorithms implemented in Python.

a hub for learning through play

In this article, we shall see how the Bayesian Kalman Filter can be used to predict positions of some moving particles / objects in 2D. This article is inspired by a programming assignment from the coursera course Robotics Learning by University of Pennsylvania, where the goal was to implement a Kalman filter for ball tracking in 2D space. Some… Read More »Using Bayesian Kalman Filter to predict positions of moving particles / objects in 2D (in R)

Interactive Lorenz attractor with 10,000 butterflies under the Lorenz attractor flow.

In numerical analysis, the Kahan summation algorithm, also known as compensated summation,[1] significantly reduces the numerical error in the total obtained by adding a sequence of finite-precision floating-point numbers, compared to the obvious approach. This is done by keeping a separate running compensation (a variable to accumulate small errors), in effect extending the precision of the sum by the precision of the compensation variable.

the official Rust and C implementations of the BLAKE3 cryptographic hash function - BLAKE3-team/BLAKE3

2.9M subscribers in the MachineLearning community. Beginners -> /r/mlquestions , AGI -> /r/singularity, career advices -> /r/cscareerquestions…

Copulas and Rank Order Correlation are two ways to model and/or explain the dependence between 2 or more variables. Historically used in biology and epidemiology, copulas have gained...

A Self-Contained Tutorial on RSA Algorithm Theories for Number Theory Noobs

The finite element method (FEM) is a popular method for numerically solving differential equations arising in engineering and mathematical modeling. Typical problem areas of interest include the traditional fields of structural analysis, heat transfer, fluid flow, mass transport, and electromagnetic potential.

An international team claims its perfect secrecy cryptography is made unbreakable by physics

An Open-Source Collection of 200+ Flash Cards to Help You Preparing Your Algorithms & Data Structures Interview 💯 - teivah/algodeck

Visualizing three, 3-dimensional strange attractors with a fractal structure as well as the differential equations that generate them.

Bloom filters (BF) are widely used for approximate membership queries over a set of elements. BF variants allow removals, sets of unbounded size or querying a sliding window over an unbounded...

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. - GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list...

Sign up with brilliant and get 20% off your annual subscription: https://brilliant.org/MajorPrep/ STEMerch Store: https://stemerch.com/ Support the Channel: https://www.patreon.com/zachstar PayPal(one time donation): https://www.paypal.me/ZachStarYT This video goes through a visual explanation of the Laplace Transform as well as applications and its relationship to the Fourier Transform. Instagram: https://www.instagram.com/zachstar/ Twitter: https://twitter.com/ImZachStar Join Facebook Group: https://www.facebook.com/groups/majorprep/ ►3D Graphing Software (this is not a sponsor nor an affiliate link, bought the software just because I liked it): https://www.runiter.com/ ►Animations: Brainup Studios (email: brainup.in@gmail.com) ►My Setup: Space Pictures: https://amzn.to/2CC4Kqj Magnetic Floating Globe: https://amzn.to/2VgPdn0 Camera: https://amzn.to/2RivYu5 Mic: https://amzn.to/2BLBkEj Tripod: https://amzn.to/2RgMTNL Equilibrium Tube: https://amzn.to/2SowDrh ►Check out the MajorPrep Amazon Store: https://www.amazon.com/shop/zachstar

Basic linear algebra can have a surprising influence on deep learning and machine learning. Learn what linear algebra is and how to use it.

Most of us last saw calculus in school, but derivatives are a critical part of machine learning, particularly deep neural networks, which are trained by optimizing a loss function. This article is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks. We assume no math knowledge beyond what you learned in calculus 1, and provide links to help you refresh the necessary math where needed.

Many former algebra students have painful memories of struggling to memorize the quadratic formula. A new way to derive it, overlooked for 4,000 years, is so simple it eliminates the need.

💻📖 Laws, Theories, Principles and Patterns that developers will find useful. #hackerlaws - dwmkerr/hacker-laws

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on DSC. The full series is accessible here.  29 Statistical Concepts… Read More »29 Statistical Concepts Explained in Simple English – Part 3

In vector calculus, the Jacobian matrix (/dʒəˈkoʊbiən/,[1][2][3] /dʒɪ-, jɪ-/) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. When this matrix is square, that is, when the function takes the same number of variables as input as the number of vector components of its output, its determinant is referred to as the Jacobian determinant. Both the matrix and (if applicable) the determinant are often referred to simply as the Jacobian in literature.[4] They are named after Carl Gustav Jacob Jacobi.

The covariance matrix has many interesting properties, and it can be found in mixture models, component analysis, Kalman filters, and more. Developing an intuition for how the covariance matrix operates is useful in understanding its practical implications. This article will focus on a few important properties, associated proofs, and then some interesting practical applications, i.e.,… Read More »Create Transformed, N-Dimensional Polygons with Covariance Matrix

Course overview Memory leaks and dangling pointers are the main issues of the manual memory management. You delete a parent node in a linked list, forgetting to delete all its children first -- and your

This theoretical physicist’s idea has an astounding legacy.

This link will take you to a page that’s not on LinkedIn

How to use polynomials to share secrets, and how to verify that the secret has been shared without unlocking it.

The Wavefunction Collapse Algorithm teaches your computer how to riff. The algorithm takes in an archetypical input, and produces procedurally-generated outputs that look like it.

A while back, there was a discussion comparing the performance of using the hashbrown crate (based on Google’s SwissTable implementation1) in the Rust compiler. In the last RustFest, Amanieu was experimenting on integrating his crate into stdlib, which turned out to have some really promising results. As a result, it’s being planned to move the crate into stdlib. I insist on watching this talk when you have some free time! ↩

A technical report on convolution arithmetic in the context of deep learning - vdumoulin/conv_arithmetic

The geometry puzzles that are lighting up Twitter.

Let's Encrypt does not currently generate Elliptic Curve certificates. Here's how to obtain one.

If you like to rely on the web to do your electronics and computer math, you’ll want to bookmark FxSolver. It has a wide collection of formulae from disciplines ranging from electronics, comp…

Computer scientists have been searching for years for a type of problem that a quantum computer can solve but that any possible future classical computer cannot. Now they’ve found one.

Last time we saw a geometric version of the algorithm to add points on elliptic curves. We went quite deep into the formal setting for it (projective space $ \mathbb{P}^2$), and we spent a lot of time talking about the right way to define the “zero” object in our elliptic curve so that our issues with vertical lines would disappear. With that understanding in mind we now finally turn to code, and write classes for curves and points and implement the addition algorithm.

A visual guide to Connectionist Temporal Classification, an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems.

A visual approach to understanding resolution based on MTF (modulation transfer function) curves.

In 1989, Kirk Lougheed of Cisco and Yakov Rekhter of IBM were having lunch in a meeting hall cafeteria at an Internet Engineering Task Force (IETF) conference. They wrote a new routing protocol that became RFC (Request for Comment) 1105, the Border Gateway Protocol (BGP), known to many as the “Two Napkin Protocol” — in reference to the napkins they used to capture their thoughts.

Fish schools, bird flocks, and bee swarms. These combinations of real-time biological systems can blend knowledge, exploration, and exploitation to unify intelligence and solve problems more efficiently. There’s no centralized control. These simple agents interact locally, within their environment, and new behaviors emerge from the group as a whole. In the world of evolutionary alogirthms… Read More »Swarm Optimization: Goodbye Gradients

In December 2017, researchers at Google and MIT published a provocative research paper about their efforts into “learned index structures”…

Which machine learning algorithm should you use? It is a central question in applied machine learning. In a recent paper by Randal Olson and others, they attempt to answer it and give you a guide for algorithms and parameters to try on your problem first, before spot checking a broader suite of algorithms. In this post, you will discover a…

Searching through millions of points in an instant

Searching through millions of points in an instant

Minimal examples of data structures and algorithms in Python - keon/algorithms

I recently ran across this bloom filter post by Michael Schmatz and it inspired me to write about a neat variation on the bloom filter that…

This article will review the basics of the decimation-in-time FFT algorithms.

Machine learning algorithms aren’t difficult to grasp if you understand the basic concepts. Here, a SAS data scientist describes the foundations for some of today’s popular algorithms.

Two of the most commonly taught data structures in computer science are the singly-linked list and doubly-linked list.

A new “shrinking bull’s-eye” algorithm from researchers at MIT speeds up complex modeling from days to hours.

Psychology Today reports: In a study conducted in Milan, Italy, and published in November 2025, the sight of a person dressed as Batman led to a nearly doubled rate of people giving up their seat to a pregnant woman. Over the course of 138 subway rides, researchers found that people who saw "Batm...

Why psychology explains politics better than politics explain psychology

Science suggests we are hardwired for altruism, but do we really need to be thinking of others all the time?

The lovely paradox of doing good in the world is that it does you good too.

Effective altruism has gone mainstream. Where does that leave it?

‘Do-gooders’ are often judged harshly. Why do we resent their acts of altruism or question their motives?

When there is an opportunity to gain a positive reputation, individuals are more willing to sacrifice their immediate self-interest. Partner choice creates opportunities for competitive altruism, i.e. individuals compete to be regarded as more generous ...

When to ask questions, and when to have answers

Web magazine about user experience matters, providing insights and inspiration for the user experience community

This report describes 12 common flaws, errors, and misadventures that occur in people’s heads when predictions are made.

Examining RDNA 4's out-of-order memory accesses in detail, and investigating with testing

Lenovo, the firm emerging as a driving force behind AI computing, has expressed tremendous optimism about AMD's Instinct MI300X accelerator.

While there have been efforts by AMD over the years to make it easier to port codebases targeting NVIDIA's CUDA API to run atop HIP/ROCm, it still requires work on the part of developers.

AMD recently unveiled 3D V-Cache, their first 3D-stacked technology-based product. Leapfrogging contemporary 3D bonding technologies, AMD jumped directly into advanced packaging with direct bonding and an order of magnitude higher wire density.

AMD is one of the oldest designers of large scale microprocessors and has been the subject of polarizing debate among technology enthusiasts for nearly 50 years. Its...

AMD ROCm documentation

Emerging evidence suggests that the brain encodes abstract knowledge in the same way that it represents positions in space, which hints at a more universal theory of cognition.

2019 UPDATE: Since this post came out, I co-authored a book about it called Super Thinking: The Big Book of Mental Models.

The rise of "zero-click" searches may signal the coming effect of AI shopping on product discovery and decision-making.

Discover which statistical methods dominate healthcare, finance, tech, retail, and sports analytics, and why these industry-method pairings became indispensable standards.

Learn what Shapley values are and how SHAP tools help explain machine learning predictions.

Learn to calculate and interpret five essential effect size measures with Python examples and clear guidance.

Learn to calculate support, confidence, and lift metrics for market basket analysis using Python's mlxtend library.

Discover hidden customer purchasing patterns with market basket analysis to optimize product placement and increase sales.

In this article, I'll take you through a practical guide to RFM Analysis using Python. A Guide to RFM Analysis using Python.

Umami is a simple, fast, privacy-focused alternative to Google Analytics. - umami-software/umami

Marketers should be wary of open-source programs promoted by purveyors with a walled garden history.

A SWOT analysis helps teams understand how well a product, service, or organization is positioned in the market to serve its customers.

Uncover deeper insights beyond ZIP codes with geospatial analysis. Explore the limitations of ZIP codes and discover alternatives for spatial understanding.

Still, the exact application, challenges and shortcuts related to this technique are relatively unknown, and that’s what this article seeks to change.

Use methods like 5-second testing, first-click testing, and preference testing to gain insights into how users perceive your visual design.

This is a repo with links to everything you'd ever want to learn about data engineering - DataExpert-io/data-engineer-handbook

GA4 provides valuable insights into user interactions on your website. Learn how to analyze key metrics like sessions, session duration, and events to refine your digital strategy.

Goodhart's Law is useless. It tells you about a phenomenon, but it doesn't tell you how to solve it. We look at how organisations actually prevent Goodhart's Law, and illustrate this with Amazon's Weekly Business Review as an example.

How to build upon a previous experiment, without throwing it all away.

Hey guys, welcome back to my R-tips newsletter. Supply chain management is essential in making sure that your company’s business runs smoothly. One of the key elements is managing inventory efficiently. Today, I’m going to show you how to estimate inve...

“If you want to change the game, change the frame.” The game has certainly changed with the data era, and maybe the most drastic change driven by data has occurred in economics, the foundation upon which our modern society is built and sustained. Understanding and mastering the transition from “traditional” economics to modern data-driven economics… Read More »Mastering the Big 12 Data-driven Economic Concepts

Learn which variables you should and should not take into account in your model.

In this article, I'll take you through the task of Customer Satisfaction Analysis with Python. Customer Satisfaction Analysis with Python.

A/B testing is a cornerstone of data science, essential for making informed business decisions and optimizing customer revenue. Here, we delve into six widely used statistical methods in A/B testing, explaining their purposes and appropriate contexts. 1. Z-Test (Standard Score Test): When to Use: This method is ideal for large sample sizes (typically over 30) when the population variance is known. Purpose: Compares the means of two groups to determine if they are statistically different. Applications: This technique is frequently employed in conversion rate optimization and click-through rate analysis. It helps identify whether changes in website elements or marketing strategies

The authoritative guide on how Amazon does WBRs (from former exec Colin Bryar): how it works, how to do it, and how Amazon uses it to win.

Create your first run chart and start interpreting your data using just four rules. Your go-to QI resource.

Analytics, management, and business intelligence (BI) procedures, such as data cleansing, transformation, and decision-making, rely on data profiling. Content and quality reviews are becoming more important as data sets grow in size and variety of sources. In addition, organizations that rely on data must prioritize data quality review. Analysts and developers can enhance business operations by analyzing the dataset and drawing significant insights from it. Data profiling is a crucial tool. For evaluating data quality. It entails analyzing, cleansing, transforming, and modeling data to find valuable information, improve data quality, and assist in better decision-making, What is Data Profiling? Examining

Visual, interactive sample size calculator ideal for planning online experiments and A/B tests.

Window functions are an advanced feature of SQL that provides powerful tools for detailed data analysis and manipulation without grouping data into single output rows, which is common in aggregate functions.

More than half of the NCAA Tournament's top teams have used HD Intelligence services, as basketball's data revolution sweeps through the college game.

At most small and medium-sized e-commerce retailers, prices are typically set and updated in an ad hoc fashion without one clear owner. The process often starts by using a gross margin target, followed by some comparison with competitors, and then some adjustments from there. Many of these retailers would quickly admit that this isn’t an optimal strategy, and that they are likely leaving money on the table — and they’re often right. The authors’ experience with price testing has shown that there is actually a significant amount of money left on the table when pricing is left un-optimized.

Knowing the URLs in search engine result pages leads to further analysis, such as referring domains, page authority, word count, and more.

Evaluating ad targeting product using causal inference: propensity score matching!

In this article, I'll take you through the task of Market Basket Analysis using Python. Market Basket Analysis using Python.

Two principles on collecting data, from the field of Statistical Process Control. As with most principles in SPC, this is both simpler and more important than you might think.

Since starting PostHog in 2020, we’ve learned a bunch about what does and doesn’t work when it comes to marketing to engineers . Paid ads is a…

Using data provided by Vivid Seats and Instagram, I learned that social media clout isn't all it's cracked up to be.

An obsessively detailed guide to Customer Lifetime Value techniques and real-world applications

These tools can help you analyze PPC competitors, track search trends or design ad creative – all without spending a dime.

For non-tech industry folks, an “A/B test” is just a randomized controlled trial where you split users or other things into treatment and control groups, and then later compare key metr…

8 stories · A guide to building an end-to-end marketing mix optimization solution for your organization.

A spreadsheet on ad platform Xandr’s website revealed a massive collection of “audience segments” used to target consumers based on highly specific, sometimes intimate information and inferences

Applying causal machine learning to trim the campaign target audience

How to compare and pick the best uplift model

Looking for the best alternative to Google Analytics 4? Here are 15 web analytics platforms you may want to consider.

Running experiments is equal parts powerful and terrifying. Powerful because you can validate changes that will transform your product for the better…

An in-depth explanation of “Thompson Sampling”, a more efficient alternative to A/B testing for online learning

An in-depth look at seven tools used by enterprises for content optimization, technical SEO, and reporting and analytics.

This article will take you through everything about Cohort Analysis that you should know. What is Cohort Analysis in Data Science?

In this article, I will walk you through the task of Retail Price Optimization with Machine Learning using Python. Retail Price Optimization.

In this article, I will take you through the task of Supply Chain Analysis using Python. Supply Chain Analysis using Python.

From Villa's weirdly disconnected midfield to Forest playing passes near their corner flags, here's what we can learn from analysing passing

How to adjust CATE to consider costs associated with your treatments

When you use supermarket discount cards, you are sharing much more than what is in your cart—and grocery chains like Kroger are reaping huge profits selling this data to brands and advertisers

Effective log management is a fundamental aspect of maintaining and troubleshooting today's complex...

Questions on A/B testing are being increasingly asked in interviews but reliable resources to prepare for these are still far and few…

An easy-to-read, highly condensed analysis of all the known, confirmed, rumored, and absolute myth-level Google ranking factors.

Using and choosing priors in randomized experiments.

Media Mix modeling, its implementation, and practical tips

A Discussion of the go-to methods for 5 Types of A/B Metrics

Learn how to build MMMs for different countries the right way

I recently rewatched "The Wire". The show's central theme is about counter-productive metrics and their corrupting influence on institutions. I've noticed hints of this pattern in software engineering, too

Software culture and the abuse of data

Use these tips to quickly analyze performance data and identify high-impact PPC optimizations that will move the needle.

In many board rooms, the most important go-to-market number this quarter is pipeline health. For some companies, the pipeline may be less clear than a quarter or two ago. Summer seasonality may play a role. Macroeconomics might also be lurking within the numbers. Pipeline fluctuations are normal. But any meaningful & unexpected surprise warrants introspection. Pipeline analysis often has four parts: Craft the sales sandwich to predict your GTM conversion rates & determine if close rates have changed in parallel.

Amazon will continue to be highly competitive. Want to be successful? Optimize your product listings to the fullest with these tips.

How today’s tech companies make data-driven decisions in Machine Learning production

While Fisher’s exact test is a convenient tool for A/B testing, the idea and results of the test are often hard to grasp and difficult to…

There is a huge and ever-widening gap between the devices we use to make the web and the devices most people use to consume it. It’s also no secret

If you go to three different analysts looking for a definition of "churn rate," they will all agree that it's an important metric and that the definition is self evident. Then they will go ahead and give you three different definitions. And as they share their definitions with each other they all have the same response: why is everyone else making this so com

Over the past few years, marketing on the web has become way too much fun. I remember trying to figure out what “hits” on awstats [http://awstats.sourceforge.net/] meant in high school, and I distinctly can recall how disappointed I was when I found out the true meaning. Nowadays,

Getting useful cancellation feedback from customers is tough. The problem is that once people have canceled, they’re no longer engaged and will rarely spend the time to give you feedback. One of the best things I’ve ever done to combat this with Bidsketch was to add a mandatory freeform text field that says: Please help… Continue reading Getting 200% More Actionable Feedback from Customers that Cancel →

Simple Analytics is a privacy-friendly and simple alternative to Google Analytics. No cookies. No trackers. No consent required from your visitors. Just straightforward analytics.

As of 2024, The Data Incubator is now Pragmatic Data! Explore Pragmatic Institute’s new offerings, learn about team training opportunities, and more.

Analyzing the SERPs for these micro intents will help you create the right content that a searcher will want to find.

Marc Andreessen famously said that for startups, “the only thing that matters is getting to product/market fit.” Product/market fit means providing enough value to enough people that the startup can…

I sit down and learn how to get insights from churn rates, conversion rates, and more to answer some important questions about my product.

    

I have a theory: No Diggity by Blackstreet is timeless. If Frank Sinatra is timeless in 2015, so too is No Diggity in 2050, fondly remembered by our children's children as the icon of the 90s. And I think that I can prove it.

Pricing is hard. Make it too low and you miss out on profit; too high and you miss out on sales. These pricing experiments will help you get it right.

this is a guest post by Kareem Mayan. customer retention was a recent topic in our predictable […]

A/B testing is hitting the mainstream because it is so effective. And with so many tools available it has become very easy and very inexpensive to run. Here are 23 helpful tips on how you can take your A/B tests from basic to the next level.

You must test ads to make your paid search account grow and thrive. That fact is no longer debatable – it is just a best practice fact. Ad testing in

A/B testing tools often lie about whether something is "statistically significant." Here's an extremely simple, mathematically sound formula to compute it for yourself.

A/B tests provide more than statistical validation of one execution over another. They can and should impact how your team prioritizes projects.

Koru CEO Kristen Hamilton helps hundreds of people hire and get hired every year. These are the traits she knows translate into excellent performance on the job.

Contributor Aleh Barysevich breaks down three strategies you can use to boost the effectiveness of your internal link building campaigns to fulfill specific SEO-related goals.

The antidote to vanity metrics when you have less than 1 hour/week for marketing analytics

Simple Analytics is the privacy-first Google Analytics alternative that is 100% GDPR compliant. Give us a try!

We’re Agile, we think lean, we’re data-driven. If you live in the new economy and work in some sort of digital product you hear some of…

An applied introduction to causal inference in tech

In "Email Marketing Metrics, Part 1: The Basics," my article last month, I addressed the primary measurements for email marketing: delivery rate, open

We spoke with Etsy’s iOS Software Engineer, Lacy Rhoades, about their culture of continuous experimentation. Learn about their a/b testing culture

There’s widespread use of adblockers on the web but users are increasingly blocking cookies and other tracking scripts too. Browsers such as Safari, Firefox and Brave are privacy-focused.

If you are working in the field of SEO or if you are managing a content or Ecommerce website then you...

A cohort is a group of people who share a common characteristic or experience within a defined period. This is a handy tool for browsing cohort datasets.

Unlock data to make effective decisions across digital marketing. SEO, content marketing, PPC, digital PR, and more.

Articles, software, calculators, and opinions.

“My biggest surprise was when we launched the Facebook app and it didn’t go viral” -Startup CEO quote “The month after we ...

Deploy and update measurement tags on your websites and mobile apps from a web interface, without major code changes or app releases.

Knowing what to test and how to interpret the results based on nuances and oddities of experiments is an important skill for people, not automations.

A/B testing is a very popular technique of checking granular changes in a product without mistakenly taking into account changes that were…

Hey everyone! I star all kinds of crazy GitHub repos and last week I stumbled on an awesome project...

Multivariate tests indicate how various UI elements interact with each other and are a tool for making incremental improvements to a design.

With the ubiquity of music access and a lack of any need for patience, the term "skip-rate" has crept into the modern music industry lexicon, and some new data behind. Continue reading

The best way to determine what works best for your site is to carry out an A/B test for your landing pages. Check out this A/B significant test calculator.

How to build a free, privacy-focused alternative to Google Analytics

Developers don’t do SEO. They make sure sites are SEO-ready. That means developers hold the key to SEO. It’s true. If you’re a developer and you’re r

Spotify analytics for listeners is how the popular streaming service also captures the hearts of its users. Many websites allow

Content marketing has become an increasingly popular way for brands to promote themselves. It is subtle and generates more leads than traditional

Search engine optimization for ecommerce boils down to four buckets. That's according to Jeff Oxford, founder of 180 Marketing, an Oregon-based firm.

Shoppers' actions on an ecommerce site create opportunities for automated, triggered emails. Such behavior-based email automation is a sure-fire tactic to drive revenue.

Monitoring rankings remains the best way to track organic search performance. In this piece, we list five helpful tools to track your site's positions and your competitors'.

Conjoint analysis is a highly effective means of market research, capable of informing a company’s pricing strategy and product development.

Conjoint analysis is the optimal market research approach for measuring the value that consumers place on features of a product or service. Learn more!

Here are four of the top technical SEO issues that your auditing tools won't show you and how to find them.

Our A/B test calculator will help you to compare two or three variants to determine which test will be statistically significant.

The way we live our lives has an impact on our work. Long lists of typical chores may turn your

Competitive poaching refers to the practice of bidding on ads for a competitor’s search terms, in order to poach customers searching for that brand. It’s a common tactic in the world of digital ads — but is it effective? The author shares results from the first-ever empirical study of this practice, which found that poaching can work well for higher-end brands, but may backfire for lower-end or mass market offerings. Specifically, the study found that when an ad poached customers who searched for a high-end brand, users clicked on it more, but when an ad poached a low-end or mass market target, users were less likely to click. Of course, the author notes that clickthrough rate is just one metric, and there may be other ways in which a poaching campaign could be harmful or beneficial. But these findings can help marketers add a bit of science to the art that is digital advertising, helping them to optimize campaigns for their unique products and customers.

Keyword lists for SEO are often cluttered and seemingly endless. "Clustering" can help by grouping keywords by a common modifier.

The Landing Page report. Universal Analytics has it. GA4 does not. But you can make it! This article will show you how.

It's time to optimize for People Also Asked questions asked around and about your brand in Google's SERPs. Here's why.

The most consistent sales leader I’ve worked with hit plan 27 consecutive quarters. How can a sales leader develop similar repeatability? Much goes into it here are the reports he used to manage his team at the board level. The PQR (pipeline-to-quota) funnel is first. Pipeline is the total value of the accounts within a stage or later. Quota is the aggregate quota on the street for the quarter. Divide P by Q to get PQR.

Tracked analytics metrics should reflect change in the user experience. Vanity metrics appear impressive, but their fluctuations are not actionable.

Elaborate usability tests are a waste of resources. The best results come from testing no more than 5 users and running as many small tests as you can afford.

Keyword Tool is #1 (FREE) alternative to Google Ads Keyword Planner for SEO & PPC keyword research ᐈ Generate 1,000s ✅ long-tail keywords in seconds!

Common mistakes to avoid when you’re getting started with experimentation

A/B testing, the process of exposing randomized visitors to one or more variables, is among the most effective strategies to optimize user experiences and conversion rates. Here is a list of A/B testing tools.

Is Google Analytics still useful and how accurate are its stats? How much data is missing from Google Analytics due to adblockers and privacy-friendly browsers?

Managing a Google ads campaign requires understanding how to check, optimize, test, and change your ads. Read this post to learn more.

Not sure where to start with marketing automation? Here are 25 tools, and how to use them to streamline and improve your marketing.

Technique used to gain insights about consumers’ preferences

Pie charts and scatter plots seem like ordinary tools, but they revolutionized the way we solve problems.

Statistics & Business can share the same Language

A new approach in the way the Census aggregates its data could make it more difficult to do extreme gerrymandering, says Moon Duchin.

In marketing analytics, conjoint analysis is a technique used to gain specific insights about consumers’ preferences. Often derived from consumer surveys, conjoint analysis can tell us, for instance…

Thirty years ago, Billboard changed the way it tabulated its charts, turning the industry on its head and making room for genres once considered afterthoughts to explode in the national consciousness

Should we still be talking about online and offline retail, or about trucks versus boxes versus bikes?

Net dollar churn is a more value-driven way of looking at churn.

Experimentation is widely used at tech startups to make decisions on whether to roll out new product features, UI design changes, marketing campaigns and more, usually with the goal of improving…

The best way to optimise your website is usually the simplest.

Free books, lectures, blogs, papers, and more for a causal inference crash course

Pandas doesn’t handle well Big Data. These two libraries do! Which one is better? Faster?

There’s a reason that online ticket sellers hit you with those extra fees after you’ve picked your seats and are ready to click “buy.” Pure profit. A

How not to fail your online controlled experimentation

Optimizing web marketing strategies through statistical testing

A/B Testing — A complete guide to statistical testing - bjpcjp/AB_Testing

Uplift models seek to predict the incremental value attained in response to a treatment. For example, if we want to know the value of showing an advertisement to someone, typical response models will only tell us that a person is likely to purchase after being given an advertisement, though they may have been likely to purchase already. Uplift models will predict how much more likely they are to purchase after being shown the ad. The most scalable uplift modeling packages to date are theoretically rigorous, but, in practice, they can be prohibitively slow. We have written a Python package, pylift, that implements a transformative method wrapped around scikit-learn to allow for (1) quick implementation of uplift, (2) rigorous uplift evaluation, and (3) an extensible python-based framework for future uplift method implementations.

A heatmap is a graphical representation of data in which data values are represented as colors. That is, it uses color in order to…

The intuitive way of A/B testing. The advantages of the Bayesian approach and how to do it.

You can say goodbye to coding for data wrangling and data cleaning

The Guide to Product Analytics taps dozens of product leaders (from companies like Google, Twitter, and LinkedIn) to break down how PMs can use product analytics to drive product-led growth.

Retail Analytics: Data Science for Retail

If you make $10 profit each time you sell a product, what cost per conversion should you aim for? Answering this question isn't easy, but it can teach us a lot about how to approach advertising.

PSL Features

Big success. Bigger failure. And lots of lessons. Learn why building a growth team may be a multi-million dollar mistake.

Every website or PWA you build should automate as much prospecting and selling as possible. The only thing is that visitors enter websites with various mindsets, depending on which part of the buying stage they’re at. This means that you can’t just take every person who enters the site through the same path. You have to design a custom sales funnel (or pathway) for each kind of buyer. In this article, Suzanna Scacca will tell you what you need to keep in mind.

Learn how to interpret what’s happening in your paid search account with your traffic, conversions and sales data.

Running an A/B test is easy. Screwing up an A/B test is even easier.

Google Analytics may be the most important application to understand the behavior of your visitors. And whether you’re a beginner or an experienced user, there are many free resources to help. Here is a list of free tutorials for Google Analytics.

There has been a seismic shift in website traffic in the past several years, from desktop to mobile. Google Analytics has rolled out the beta version of cross-device reporting to inform merchants of how their shoppers are interacting via multiple devices.

Increasingly, companies are using experiments to guide them in their decision making—but many are still missing opportunities, or are failing to implement experiments well. When it comes to the rollout of new products, one particularly effective new kind of experiment involves randomizing the introduction of new products across a set of markets. Uber used this strategy before rolling out its Express Pool service, and Airbnb did the same before rollout out a new landing-page design. In both cases, the companies gathered data that allowed them to roll out their products with confidence that they would succeed—as indeed they did. Many companies, even those not in the tech sector, can benefit from this kind of experimentation, especially if they follow a few basic guidelines.

When we think about the data we hold on our services, the first thing that comes to mind is often website analytics. But there are other valuable and occasionally overlooked types of data that can be really useful to user researchers.

How I replaced Google tracking with simple log-based analytics on my personal website.

Google Analytics is a powerful, free web analytics platform. However, it has gaps that are better served by other tools. I'll address those gaps and tools in this post.

Update 2016-10-18: This tutorial has been updated to reflect the latest version of my stack (now with Drip!). I’ve also updated pricing info (it’s technically a $0 stack now) and screenshots. The original outdated article is archived here. “Just tell me what to do so I can stop

“That’s just one person” and “Our real users aren’t like that” are common objections to findings from qualitative usability testing. Address these concerns proactively to ensure your research is effective.

Last week we hosted over 130 experimenters at Optimizely HQ in San Francisco for our first live event of the year. We were lucky enough to be joined by two...

Finding and building the next big idea is the holy grail of any tech company. Unfortunately the statistics are against us: when subjected…

Check out these 3 privacy-focused alternatives to Google Analytics.

Connect with developers sharing the strategies and revenue numbers behind their companies and side projects.

When we need to measure marketing campaigns, most of us have cracked online campaign tracking – we have a cookie

The biggest question in ecommerce A/B testing is not “how.”

A side project that got much bigger than I thought.

Read this guide for an overview of Google Analytics and how you can use all the data to your advantage to boost your SEO and digital marketing.

Sammy Gelfand is the numbers guy behind the Golden State Warriors’ success. Some pretty good players help, too.

Learn how the world's fastest growing companies have hacked their way to success with innovative products, viral promotions and ingenious marketing campaigns. [6500 words]

A/B tests are controlled experiments of two attributes, to measure which one was most popular with users. You can apply A/B testing to just about anything that you can measure. Multivariate testing allows you to measure multiple variables simultaneously.

We will review another fascinating approach that marries heuristic and probabilistic methods. We will link marketing channels with a probability of a customer passing through each step of a Sales Funnel

When deciding whether to track users on the server or on the client, there are many gotchas and factors to consider. Here is a short guide with pros and cons of each.

Data Science, Machine Learning, AI & Analytics

At some point, almost every company faces questions like How good are the customers that we acquire? How do they

Users are rating items on your website. How do you know what the highest-rated items are?

Plus, the personality traits associated with activism

Go ahead, get mad. It’s healthy.

At the top of the world, the Inuit culture has developed a sophisticated way to sculpt kids' behavior without yelling or scolding. Could discipline actually be playful?

Anger is a fuel that’s dangerous when out of control. But managed well, it can energise you to identify and confront problems

Anger is temporary madness: to avoid the triggers, follow the Stoics’ advice and achieve a kind of serenity

A common reason why an Angular bundle is bloated is that it uses a library like MomentJS that isn't...

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

You've been given an Angular code base. How do you figure out where everything is? Where scope variables are coming from? What controller does what? Angular doesn't make it easy, but there are few tips and tricks that can make your life easier. Tools like Angular Batarang can help, but

Angular 13 Starter with Material, Transloco, Jest, Compodoc, Docker Support, ESLint &...

Starter project with Angular 13, Ngx-admin, NestJs, Nx Workspace, Jest, Cypress, ESLint &...

The 9.0.0 release of Angular is here! This is a major release that spans the entire platform, including the framework, Angular Material…

AngularJS is a magic framework. Using it well will drastically improve your productivity, code modularity and reusability. Using it badly…

I am new to Angular (even though I am not new to the web development), so please take everything that I am about to say with a grain of salt. That being said, I watched a lot of talks and read a lot of articles relevant to Angular performance, and this post is the summary […]

CLI tool for Angular.

Angular is a platform for building mobile and desktop web applications. Join the community of millions of developers who build compelling user interfaces with Angular.

🕑 The Wait Is Over ❕

Angular Style Guide: A starting point for Angular development teams to provide consistency through good practices. - johnpapa/angular-styleguide

Learn to create interesting biological models and graphics using SVG and AngularJS

How to create simple CI/CD pipelines for automated deployments

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

"Framework is heart of every technology." Whether you are a beginner, a senior developer, a freela...

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

The web development framework for building modern apps.

Top favorite Angular libraries and tools you should definitely try.

Create new Angular 2 applications, scaffold components, run tests, and build for production with Jurgen Van de Moere's guide to Angular CLI

55K subscribers in the angularjs community. A community for the awesome MVC JS framework.

This is a comic about naked mole rats, aka tube goblins.

Killing the predators is not nearly as effective as the intimidating presence of well-trained guardians, a role some breeds have played for 5,000 years

The secrets to extending human lifespans might lie in the animals that can already live for centuries.

Are people crying Bigfoot when it’s really a bear?

Following the Life of an Abandoned Bull in Nepal

Insects that tuck away wings; a protist with an accordion-like neck — studying these clever creases may inspire foldable structures for drones

Although "dog" is ubiquitous today to describe man's best friend, it remains a mystery where the word originally came from.

After a decade of carnage, we finally know what’s devastating sea stars along North America’s West Coast. Does that mean scientists can save them?

Every night, a male leopard seal slips off the ice and sings underwater for hours. It sounds structurally like a human nursery rhyme...

Insects are among the oldest of weaponry

A new study shows bonobos can combine vocal calls in ways that mirror human language, producing phrases with meanings beyond the sum of individual sounds. "Human language is not as unique as we thought," said Dr Melissa Berthet, the first author of the research from the University of Zurich. Another...

More than a century after the invention of vaccines, a veterinarian stumbled across a technique to boost their efficacy in an unlikely way — by observing wounded horses.

300 aspects of each call were cataloged, letting researchers estimate meaning.

The luxury tuna industry is killing the Mediterranean.

The convoluted story of how a species of dog first arrived in Australia and subsequently took over the Outback challenges fundamental notions about what it means to be “native.”

Violence is written in their genes.

Jennifer Dunn, the artist behind the Instagram account Mossy Hollow, characterizes her work as "Watercolor meme art," a distinctive blend of pop culture referen

For much of human history, wolves and other large carnivores were considered pests. Wolves were actively exterminated on the British Isles, with the last wolf killed in 1680. It is more difficulty to deliberately wipe out a species on a continent than an island, but across Europe wolf populations were also actively hunted and kept

Once, the red wolf roamed every Southern state. Today, only seventeen remain in the wild on a swampy peninsula in Eastern North Carolina, a number on the rise thanks to the passionate team of biologists determined to help them thrive once more

What snakes, ferrets, and elephants are revealing about cancer resistance

After a decade of elusive wildlife trafficking, we traced one anonymous dealer to a house in Malaysia, all thanks to a customer complaint.

Horses bled for antivenom, crabs drained for endotoxin tests, and silkworms boiled for silk. Science can now replace these practices with synthetic alternatives — but we need to find ways to scale them up.

In Hawai‘i, people, pigs, and ecosystems only have so much room to coexist, and the pigs exist a little too much.

The Whip-Poor-Will’s shrill, death-proclaiming song populates the works of Stephen King and H.P. Lovecraft. But the bird itself has fallen on hard times. Could it become a ghost of Halloweens past?

The entire world’s population of Przewalski’s horses once dwindled to a mere dozen. So how did a pair named Fiona and Shrek end up in livestock auctions in the West?

The birds were accidentally poisoned in India. New research on what happened next shows how wildlife collapse can be deadly for people.

Researchers say the nearly mile-long swim was the longest by big cats ever recorded.

By performing tricks for birds, monkeys and other creatures, researchers hope to learn how they perceive and think about their world

Research on the rumbles of wild elephants suggest that these animals address each other with unique, name-like vocalizations. (Story aired on All Things Considered on June 10, 2024.)

And the people trying to save these endangered species.

Some scientists think the radioactive, human-free landscape might now be a haven for plants and animals.

Where once there was cattle and horse rustling, the American West is now confronting the theft of its bees.

Bachman’s warbler is one of 21 species declared extinct last year – but scientists are still discovering its secrets

If we can learn to speak their language, what should we say?

Experts warn it's "boom time" for invasive species like the Asian hornet. But some native bee species are learning to fight back.

Rats are less pestilent and more lovable than we think. Can we learn to live with them?

Contrary to popular lore, insects do not confuse artificial light for the moon

The captivating horror of category violation.

The birds can associate images with distinct reward probabilities.

A conservation N.G.O. infiltrates wildlife-trafficking rings to bring them down.

The first piece in our new series on species interconnectedness traverses through the 60-million-year-old evolution of bats and moths.

Ocean creatures soak up huge amounts of humanity’s carbon mess. Should we value them like financial assets?

In the woods near her home, Lucy Jones discovers the magic of slime molds and becomes entangled in their fluid, nonbinary way of being.

Language lessons with an extraordinary ape.

Some organisms truck along slowly for aeons before suddenly surging into dominance – and something similar often happens with human inventions, too. But why?

The purpose of play — for children, monkeys, rats or meerkats — has proved surprisingly hard to pin down. Scientists continue to toss around ideas.

Wolves are my favorite animal, but my parents see them as the enemy that kills their livestock

What can elephants, birds, and flamenco players teach a neuroscientist-composer about music?

Why fly all the way across the ocean when you can chill out by the pool?

Animal ‘personalities’ are forcing scientists to rethink basic research.

A secret pattern links far-flung octopus limbs

Pets left behind when people fled the disaster in 1986 seem to have seeded a unique population.

A woman, an elephant, andan uncommon love story spanningnearly half a century.

Disgust is surprisingly common across nature.

The story of Lacey, and why I had to kill her.

Catapult publishes literary fiction and artful narrative nonfiction that engages with our Perception Box, the powerful metaphor we use to define the structure and boundaries of how we see others in th

Data suggests brands can blunt public awareness of species loss when they use at-risk animals in ads. Should they pay?

Defining what a dog is is really tough, but the domestication of wolves might be the feat that set modern humans on the path to dominance

Advanced technologies like A.I. are enabling scientists to learn that the world is full of intelligent creatures with sophisticated languages, like honeybees. What might they tell us?

Master falconer Alina Blankenship and her mélange of raptors have become the protectors of some of Oregon's top vineyards.

By counting the facial neurons in African savanna and Asian elephants, researchers made a discovery about the animals’ trunks.

They can fall from potentially infinite heights and survive. They can pivot off of nothing to land on their feet. Scientists still can’t fully explain why.

Behold choanoflagellates, tiny creatures that can be one body and many bodies all at once.

People say farmers aren’t supposed to get emotionally attached to livestock. Uh-huh. When fate sent our writer two newborn sheep with life-threatening birth defects, that kind of thinking was banished from the barn.

It got too cozy with its host.

To save endangered eels, researchers have been working for decades to figure out where they reproduce.

Some cats do it, but others can’t—and researchers still don’t fully understand why.

In the Panhandle, where swarms of lionfish gobble up native species, a tournament offers cash prizes to divers skilled at spearing one predator after another.

Scientists are using machine learning to eavesdrop on naked mole rats, fruit bats, crows and whales — and to communicate back.

Meet the footballing bees, optimistic pigs and alien-like octopuses that are shaking up how we think about minds.

Oceans also have their vigilantes.

Famed American biologist Patricia Wright explores an astonishing breadth of biodiversity in the wilderness of Madagascar

They’ve roamed free for hundreds of years, but is that freedom harming the ecosystem they call home?

Octopuses are problem-solvers, mischief-makers and notorious escape artists. They also appear to have a rich inner life – so what is it like to be an octopus?

Hidden in the tusk of a 34-year-old mastodon was a record of time and space that helped explain his violent death.

Science News, Physics, Science, Philosophy, Philosophy of Science

In his new book, An Immense World, science writer Ed Yong explores the diversity of perception in the animal world — including echolocation, magnetic fields and ultraviolet vision.

Meet the footballing bees, optimistic pigs and alien-like octopuses that are shaking up how we think about minds

Every creature lives within its own sensory bubble, but only humans have the capacity to appreciate the experiences of other species. What we’ve learned is astounding.

Three sisters braved lions, crocodiles, poachers, raging rivers and other dangers on a 1,300-mile transnational effort to forge a new dynasty.

What happens when we talk to animals?

Wildlife crossings cut down on roadkill. But are they really a boon for conservation?

Nonhuman creatures have senses that we’re just beginning to fathom. What would they tell us if we could only understand them?

In December 1997, a tiger prowled the outskirts of a small town in Russia's Far East. In his book The Tiger, John Vaillant re-creates the events of that terrifying winter in an environment where man and tiger live side-by-side.

Hi Quartz members,

You might consider them flying rats, but their odysseys stump scientists

An ambitious project is attempting to interpret sperm whale clicks with artificial intelligence, then talk back to them.

Conservationists saw the 6-year-old brown bear as a symbol of hope. Villagers saw him as a menace. Then he turned up dead.

Your obnoxious neighbor or just a misunderstood, displaced seabird?

Zito Madu in pursuit of London’s wildlife.

Introduces the elephant ethogram: A Library of African Elephant Behavior

An anonymous reader quotes a report from Scientific American: Elephants possess an incredibly rich repertoire of communication techniques, including hundreds of calls and gestures that convey specific meanings and can change depending on the context. Different elephant populations also exhibit cultu...

The long read: Dumba has spent her life performing in circuses around Europe, but in recent years animal rights activists have been campaigning to rescue her. When it looked like they might succeed, Dumba and her owners disappeared

Machine-learning algorithms can quickly process thousands of hours of natural soundscapes

Deer can regrow their antlers, and humans can replace their liver. What else might be possible?

While captive in a Navy program, a beluga whale named Noc began to mimic human speech. What was behind his attempt to talk to us?

Artificial intelligence may help us decode animalese. But how much will we really be able to understand?

Millions suffered through terror and upheaval in the turbulent years following the Soviet occupation of Afghanistan. One of them was a baby elephant from India — A new story from India to the world, each week on FiftyTwo.in

The descendants of pets abandoned by those fleeing the Chernobyl disaster are now striking up a curious relationship with humans charged with guarding the contaminated area.

The microscopic animals can withstand extreme conditions that would kill humans, and may one day help in the development of Covid vaccines. How do they do it?

As a reptile-obsessed teen, I ran away to hunt lizards in the Everglades, then hatched a plan to milk venom from deadly snakes. It went even more comically wrong than you're thinking.

Birds do it. Bees do it. Learning about the astounding navigational feats of wild creatures can teach us a lot about where we’re going.

Nearly a century after the last wolf was eradicated in the state, a lone female arrived and established a pack. Not everyone is cheering

Animals are teaming up to adapt to a changing world.

A decade ago, scientists worried the lion could go extinct in Kenya by 2020. But today the area’s lion population is thriving thanks to an extraordinary group.

Ants show that emergency exits can work better when they’re obstructed.

In Alaska, one of the longest-running and most comprehensive seabird monitoring projects is equal parts tedium, adventure, truth, and beauty.

What will we lose when Najin and Fatu die?

The giant squid has taken on a near-mythical status for generations of sailors, explorers, and writers. How could something so big remain unseen—or be less understood than dinosaurs?

It’s dangerous to blame the decline of one species on a single predator. We humans like to do it anyway.

A chance encounter and shared moment with one of natures greatest and most fleeting phenomena. Facebook: Islands And Rivers For licensing information contact Dale Dobson - dale@iconiclinx.com

The book Honeybee Democracy, published in 2010, has been sitting on my shelf for many years.

Despite their wacky brains, these intelligent animals seem to respond to the drug in a very similar way to humans.

They’re tiny and they hover, and they’re one of only three groups of birds that are vocal learners. They sing with their mouths andtheir feathers. No wonder UC Riverside researcher Chris Clark is obsessed with hummingbirds.

What creatures live in the depths of the sea? Manatees go about 6 meters into the depths of the water. Polar bears will dive down as far as 24 meters. A thick-billed murre, which is a bird, will search for food as deep as 210 meters.It's a long, long way down past that. Neal Agarwal, who previously brought us a scroll-able scale model of space, now offers the s...

He was the alpha male of the first pack to live in Oregon since 1947. For years, a state biologist tracked him, collared him, counted his pups, weighed him, photographed him, and protected him. But then the animal known as OR4 broke one too many rules.

At a time of unprecedented mass extinctions, no animal epitomizes the global biodiversity free fall more than the Asian elephant. Paul Kvinta travels to Laos to visit a moon-shot project aimed at saving the country's 400 remaining wild behemoths, investigate the strange underworld of wildlife trafficking—and make a very unexpected purchase.

My father always pampered his pets. So when he fell ill and moved in with us, it was no surprise that his corgi came to rule our home. What I didn’t expect was for Trilby to care for me after Dad was gone.

"She's missing. I’m not going to quit her."

Self-replicating, bacterial life first appeared on Earth about 4 billion years ago. For most of Earth’s history, life remained at the single-celled level, and nothing like a nervous system existed …

In an era of climate change, everything feels strange. Even the places we call home.

Wild mustang populations are out of control, competing with cattle and native wildlife for resources. If the federal government doesn’t rein them in, ranchers may take matters into their own hands.

Go behind the scenes at the South Carolina Aquarium's Sea Turtle Care Center during a nearly yearlong journey to get a massive injured loggerhead back home

A massive collection of dog tumor samples is revealing the secrets of a contagious, parasite-like cancer that could help explain human cancers too.

The long read: In Iceland, the harvesting of these precious feathers has created a peculiar bond between human and duck. What can this unique relationship teach us?

A tour of a graveyard for beloved animals.

Technology can displace the cow and save the climate. But we will need to think beyond the bun

Kathi Lynn Austin is on a global chase to stop the flow of guns threatening to wipe the rhinoceros off the face of the Earth.

Human hunters moved north into what would become Montana on the heels of the receding ice, coming into the Mission Valley when the land was yet raw and studded with erratics. Only the first scrim o…

The female brown Aspin was found drifting in the Gulf of Thailand on Friday. It is unknown whether the dog swam the astonishing distance from the shore, or jumped off a boat at sea.

When foxes nearly wiped out a colony of little penguins, a sheepdog saved the day.

When a massive Caribbean volcano erupts, the island’s residents flee, leaving their beloved animals behind. As pets and livestock are…

Long live the red wolf.

I brought a seasoned veteran of the conflict in Afghanistan into my home—and then things got wild

Attacks by elephants on villages, people and other animals are on the rise. Some researchers are pointing to a species-wide trauma and the fraying of the fabric of pachyderm society.

They worm into snails and infect the brains of fish. They’ve also found their way into Kevin Lafferty’s heart. He sees them as beautiful examples of sophisticated evolution, and as keys to ecosystem balance.

This is the feel-good documentary we all need

The eight-legged weavers have been hunting insects for almost 400 million years, flaunting their long history in a rich array of architectures. Scientists are still figuring out the taxonomy of them all.

Behold the marvel of the animal’s fabrication.

Elephants might have the necessary capacities for personhood – we just need to help them acquire the cognitive scaffolding

Without a good shoeing, a horse can indeed be lost. Enter the farrier.

Multimillion-dollar sales of songbirds heap pressure on species already in decline. We go inside the covert investigation to capture traffickers.

A quest for tigers in India.

A new book from Christopher Skaife is a beguiling, fascinating, and highly amusing account of the strangely magical birds.

Can we use the tools of psychology to understand how colonies of social insects make decisions?

Some of the bowhead whales in the icy waters off of Alaska today are over 200 years old

The long read: Abandoned as a child, Marcos Rodríguez Pantoja survived alone in the wild for 15 years. But living with people proved to be even more difficult

A profile of a pig.

Glory, grief, and the race for the Triple Crown.

A massive raid on a long-running cockfighting ring in Arkansas has raised complex questions about ICE, immigration, and the future of a centuries-old tradition.

Rob Wielgus was one of America’s pre-eminent experts on large carnivores. Then he ran afoul of the enemies of the wolf.

New Caledonian crows were trained to seek rewards by tearing paper of a certain size, demonstrating what researchers say is quite advanced toolmaking.

Hotels, shops, bars, restaurants — dogs are welcomed warmly just about everywhere. For Pip (a.k.a. Pierre), the prancing was never better.

Fishing gear can pose a deadly threat to whales—and to those who try to save them.

The obvious answer is five: vision, hearing, touch, smell, and taste. But the reality may not be so simple.

One of the most wondrous markers of the end of the day is a murmuration of starlings

Most new diseases have their origins in animals. So why aren’t we paying more attention to their health?

Over the past four centuries quadrillions of ants have created a strange and turbulent global society that shadows our own

Whilst Europe grapples with how to deal with growing wolf populations, this mountainous region of Portugal has coexisted with the predators for centuries.

In the 1970s, a small group of Greenpeace activists had a unique idea for how they could put an end to commercial whaling.

In this article, pioneering author and web designer [Andy Clarke](https://stuffandnonsense.co.uk) shows his techniques for creating [Toon Text titles](https://stuffandnonsense.co.uk/toon-text/index.html) using modern CSS and SVG.

Plus: newsbits.

SVGs, they scale, yes, but how else can you make them adapt even better to several screen sizes? Web design pioneer Andy Clarke explains how he builds what he calls “adaptive SVGs” using ``, ``, and CSS Media Queries.

Exploring SVG and its visual effects applications

How an image format changed the way we communicate

Keeping characters looking the same across different scenes and styles has always been tricky. But now, with the new Midjourney

Something happened earlier this year where I got on a run making checkbox animations and just couldn’t stop.

Video and audio recordings of people saying or doing things they never said or did can be created using AI deepfake generators and software tools that use artificial intelligence to make convincing fakes. A neural network is trained using a massive collection of authentic media featuring the target individual to accomplish this. The web is trained to recognize individuals and imitate their appearance, speech, and behavior. There is a wide range of potential good and bad uses for AI deepfake generators. You can use them to make comedic videos or instructional materials. Here are some AI deepfake generators for photos

Geoff Bailey and Lucy York Struever used C.G.I. to create a world that’s layered and cozy, even when Death comes knocking.

Browse MakeaGif's great section of animated GIFs, or make your very own. Upload, customize and create the best GIFs with our free GIF animator! See it. GIF it. Share it.

In the ever-evolving landscape of web development, creating captivating user experiences is a...

Introduction Cascading Style Sheet (CSS) is a style sheet language that's used to design,...

1. Animated Background with SVG in CSS Output Source Code 2. CSS...

Live Demo / Download -- In this tutorial, we will utilize the power of HTML canvas to...

Since the moviegoing public first started hearing it twenty years ago, Wes Anderson's name has been a byword for cinematic meticulousness.

Javascript animation engine

Learn how to use JavaScript to draw any regular shape to a HTML canvas with a single function, and how to modify it to draw multiple shapes.

Lerp is the nickname for Linear Interpolation between two points. It's a fairly simple effect to implement but can really improve the look of your animations if you're moving an object from a point A to point B.

Web Animations API is a JavaScript API that provides a standardized approach to creating and...

For the longest time, developers were limited to Flash players and gifs when they wanted to display...

SVG `` provides a way to define how an element moves along a motion path. In this article, Paul Scanlon shares an idea of how to use it by animating race cars in an infinite loop as easy as one-two-three!

Developers often feel discouraged from editing SVG markup and experimenting with SVG animations, thinking it’s a significant time investment or they need to use a complex animation library to do so. In this article, Adrian showcases his favorite tricks, which make the process streamlined and fun.

Smashing Magazine — front-end, UX and design for front-end engineers and designers

Some of the best animation software are Visme, Adobe Animate, Blender, Pencil2D, Animaker and Biteable. Find out how these and other tools compare.

A React+D3 animated bubble chart.

Welcome to the second tutorial in this series on animating with anime.js! In the previous post,...

Let’s get things moving! 🎞

Animation can help people make sense of all the data at their fingertips.

From sequence to shot to frame, explore our studio pipeline.

Nowadays it’s hard to impress or even surprise with an interface animation. It shows interactions between screens, explains how to use the…

Used correctly, it can capture audience attention, make your website more engaging, and even improve your chances of delivering conversions for your clients.Unfortunately, like many things in the web design world, it’s also easy to get too carried away with animation. As professional designers and…

Motion is a powerful tool to attract users’ attention. When designing an animation consider its goal, its frequency of occurrence, and its mechanics.

This collection of the best JavaScript animation libraries will help you get a headstart in animating any element on your website.

Oh, animation… we want to get it right so badly, don’t we? I mean, does anybody really enjoys a stiff, snappy UI? Can anyone admit they’re…

Transitions from one CSS style configuration to another can be animated using CSS animations. A style...

Its popularity fluctuates, but it’s always there somewhere, as an essential component in any web site.From tiny, barely visible, loading spinners, to whole page transitions like a movie experience, animation reaches into every area of our designs.For designers looking to incorporate animation,…

Introduction Libraries help us to code faster through their predefined classes for...

Here is the list of awesome CSS animation resources that will help you to animate components quickly...

This comprehensive guide shows how to use CSS transitions! A back-to-basics look at the fundamental building blocks we need to create microinteractions and other animations.

From Bugs Bunny to Spike Spiegel to Miles Morales, retracing 128 years of an art form that continues to draw us all in.

The Freedom to Create

Python has some great data visualization librairies, but few can render GIFs or video animations. This post shows how to use MoviePy as a generic …

If you’re interested in creating content to promote your product or service, think about making a cartoon. Producing animation has several advantages over

what 98,000 flashcard reviews and japanese taught me about learning with llms

Lifehacker reader Gabriel Wyner was tasked with learning four languages in the past few years for his career as an opera singer, and in the process la

Identify relevant subspaces: subsets of features that allow you to most effectively perform outlier detection on tabular data

An interpretable outlier detector based on multi-dimensional histograms.

Basics of anomaly detection, its use-cases, and an implementation of simple yet powerful algorithm in Python

Discover how to effectively detect multivariate outliers in machine learning with PyOD in Python. Learn to convert anomaly scores to probability confidence, choose the best outlier classifier and determine the right probability threshold for improved model accuracy.

Utilize Anomalib from Intel OpenVinoToolkit to benchmark, develop, and deploy deep learning based image anomaly detection

Ensuring your business is proactive and risk-proof.

Let’s catch those high-dimensional outliers

Machine learning-based outlier detection

Note. This is an update to article: Using R and H2O to identify product anomalies during the manufacturing process.It has some updates but also code optimization from Yana Kane-Esrig( https://www.linkedin.com/in/ykaneesrig/ ), as sh...

Elliptic Envelope and IQR-based detection

**Anomaly Detection** is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation. [Image source]: [GAN-based Anomaly Detection in Imbalance Problems](https://paperswithcode.com/paper/gan-based-anomaly-detection-in-imbalance)

There are many techniques to detect and optionally remove outliers from a dataset. In this blog post, we show an implementation in KNIME Analytics Platform of four of the most frequently used - traditional and novel - techniques for outlier detection.

Numenta created the open source Numenta Anomaly Benchmark (NAB) to test and their own anomaly detection algorithms. Learn more about how Numenta and Domino worked together to develop the NAB.

The design taps into a growing demand for low-pressure public spaces, as digital life reshapes how people interact.

Inside the world of extreme-privacy consultants, who, for the right fee, will make you and your personal information very hard to find

How a privacy researcher proved a politician wrong, and how she created the first ever definition of anonymity in the process.

A new attribution approach uses large sets of anonymized data to infer which channels and campaigns led to conversions.

"But why?!" is a question I often find myself asking Vollebak when they create some of their oddly fascinating garments. A glow-in-the-dark puffer, a jacket that can survive mars, another garment literally made from woven metal, Vollebak tends to push the limits of what materials can be incorporated meaningfully into fashion. Their latest apparel? A

Users adopt the alias “momo” as a way to speak more freely, evade harassment, and protect personal privacy on Douban and Xiaohongshu.

Gen Z would rather be anonymous online.

You can find deep, lasting happiness in a good deed that no one knows you did.

What your generosity signals about you.

Consumers are more likely to buy embarrassing products when their embarrassment is mitigated by more-anonymous packaging. Specifically, consumers found products packaged in boxes with cool colors, small lettering, and a picture of the product to be more anonymous (and appealing) than products packaged in pumps or tubes with warm colors, medium or large lettering, and no picture. The findings show that the more anonymous a product looks, the less embarrassing a consumer finds it, and the more likely they are to purchase it.

The cron module in Ansible lets you run and manage the cron jobs on remote systems.

The fetch module allows you to get files from remote nodes. Here are some practical examples of using this module.

Make your Playbooks more readable and maintainable using Blocks feature in Ansible.

Introduction: The software development process has been transformed by the DevOps...

🔐 Introduction to Ansible 🔗Related content You can find repo...

Ansible What is Ansible? Ansible is an open-source IT Configuration...

Preparing your Infrastructure as Code solution? Ansible and Terraform are two of the most popular choices. But what's the difference?

This post was originally published on November 12, 2020, but the content has been updated according to the recent Ansible changes. In our previous blog post , we looked at what configuration management tools bring to the table. And in this post, we will take a closer look at Ansible, our configuration management tool of choice. So if you want to learn what Ansible is, what it does, and how it works, this is the post for you.

Ruby on Rails deployment using Ansible - with Lets Encrypt, Sidekiq, PostgreSQL, nginx & puma - EmailThis/ansible-rails

Ansible for DevOps examples.

Deriving the basic mathematical properties of the Smith chart from electrical engineering

In this roundup, we spotlight small, medium, and large antenna announcements fortifying communication across industries, from drones to satellites.

MIT researchers developed a method to design and fabricate reconfigurable antennas with adjustable frequency ranges. Users can adjust the frequency by squeezing, bending, or stretching the material, making the antenna more versatile for sensing and communication than traditional static antennas.

If you don’t mind massive ground antennas and fried birds, that is

THz radiations finds unique applications in astronomy, medicine and communications, but not without its own distinct challenges.

Digital radar, satellite configurations, distributed apertures and all range radar.

Understanding the engineering behind how your car can see, adapt and save your life.

How to design the perfect chirp signal for distance and velocity measurement.

A brief introduction to antennas, superheterodyne receivers, and signal modulation schemes.

In this article, we use the concept of magnetic field energy to explore the relationship between a core's hysteresis loss and its B-H curve.

How TCP interacts with the characteristics of the Starlink service.

Ordinarily, in order to establish communications at locations such as disaster sites, rescuers have to transport and set up relatively bulky, costly satellite dishes. Soon, however, a simple tubular antenna made of woven strips of material may get the job done.

Modeling electric and magnetic fields

Learn about slot antennas, namely their history, characteristics, and electromagnetic (EM) behavior for low-voltage, small-form-factor electronic devices.

The latest wireless protocol ditches radiation and focuses on a new medium: your body.

Learn more about RF wave reflection parameters, namely mismatch loss and mismatch uncertainty.

Learn about voltage standing wave ratio (VSWR), return loss, and mismatch loss, which helps characterize the wave reflections in a radio frequency (RF) design.

Aimed at improving sensing and imaging systems, Princeton University researchers have developed a reconfigurable antenna based on origami.

This e-book explores microstrip antenna design, highlighting the single-element rectangular microstrip antenna and antenna arrays constructed from single microstrip elements.

Antennas are used to transmit and receive electromagnetic energy. This article covers basic antenna theory.

If the company's technology lives up to its promise in a commercial setting, Cohere will be hard to resist or ignore.

This article explores the Butterworth low-pass filter, also known as the maximally flat filter, from the perspective of its pole-zero diagram.

Antennas allow information to be transferred to distant locations. In the second part of this Antenna Basics series, you will learn more about the physics of how antennas work.

For the first time, a beam-steering antenna is integrated into the metal casing of a mobile phone

5G Beamforming Antennas Create Design, Test Problems Assuring quality under changing conditions with shifting standards and use models is a major challenge.

Antenna Design Grows Up Modern electronics relies heavily on antennas, but companies still make mistakes. That's about to change.

This article introduces the Nyquist plot and explains how to interpret this alternative method of visually evaluating a system’s frequency response.

An intuitive tutorial of antennas and antenna theory. This website is designed to present a comprehensive overview of antennas, from design, to measurement and theory. Unnecessarily complicated math is avoided throughout.

Millimeter wave frequencies have the potential to provide a solution to the growing demand for bandwidth and high-speed communication needs.

A Faraday cage is an enclosed space with an outer layer that conducts electricity. The physical shape of the Faraday cage does not matter: it can be spherical, cylindrical, or a box. Either the cage itself can be made of a conductive material, or the cage can be built of a non-conductive material such as wood and then

Short introduction to multiple input multiple output (MIMO) radar antenna arrays

The breakthrough is taking full advantage of the orbital angular momentum properties of a coherent light source, thus enabling multiplexing.

5G is gearing up to be the most extensive implementation of mesh networking ever, and that could mean antennas will not need to broadcast for miles, just far enough to reach some devices. That unsi…

A special kind of origami folding called Miura Ori could help make antennas that can block out certain radio frequencies or next-gen cloaking tech.

Compact, inconspicuous antennas could increase cell coverage transparently

The achievement could open a new swath of spectrum for wireless networks

Breakthrough technology could help usher in 6G speed internet. Here's how it works and what it could mean for businesses.

Folding antennas into different shapes to create near infinite radiation patterns.

Genetic and anatomical data reveal how the human pelvis acquired its unique shape, enabling our ancestors to walk on two legs.

Millions of people have lost their sense of smell to COVID-19. Anthropologists are investigating the significance of this underrated sense.

The long read: For decades, anthropologists have been telling us that it’s often the informal, unplanned interactions and rituals that matter most in any work environment. So how much are we missing by giving them up?

Netflix is driving the Hollywood end game, likely confident it can increase the value of IP, and fend off YouTube.

Competition makes capitalism work. A new method for measuring it may be the holy grail of economic regulation.

Hotels and landlords can mitigate legal risks by choosing decentralized revenue management systems that use public data.

AI algorithmic collusion challenges traditional antitrust law. Legal AI frameworks adapt to prosecute self-learning pricing tools

Conventional antitrust enforcement tries to prevent harmful mergers by blocking them but empirical evidence shows that rival stock prices often rise when a merger is blocked—suggesting that many blocked mergers would have increased competition. In other words, we may be stopping the wrong mergers. In a clever proposal, Ayres, Hemphill, and Wickelgren (2024) argue that […]

The tech giant, which wrapped up its arguments in the federal monopoly trial, simply says it has the best product.

If the Justice Department sues Live Nation and Ticketmaster, it will be armed with antitrust arguments. But the defendants will have defenses ready.

With a single scholarly article, Lina Khan, 29, has reframed decades of monopoly law.

The DOJ wants to show Google can do this because it has a monopoly.

The DOJ and Google faced off in a 10-week trial.

A production-tested take on GraphQL in enterprise systems, why the honeymoon phase fades, and when its complexity outweighs the benefits.

As it turns out, OpenAI’s rate limits are a little more complicated than other APIs.

Even now in 2024, there are still fundamental issues with GraphQL.

Understand the most common API vulnerabilities, how cybercriminals are targeting them and what you can do to prevent them.

Smudge.ai is a Chrome extension that gives you ChatGPT-powered shortcuts in your right-click menu.

A Fun Tutorial using Python, JSON, and Spotify API! You might find it more comfortable...

Bookmarking service

A complete beginner-friendly introduction with example code

Web Animations API is a JavaScript API that provides a standardized approach to creating and...

Here are top 10 Web APIs for your web projects. 1) Fake Store API: The Fake Store API is...

In this tutorial we’ll be using the HTML Geolocation API to display the current location of a user on...

With the rapidly changing technologies, developers are being provided with incredible new tools and...

The InfoSec community is highly active on Twitter. The platform is, among other things, used is for sharing malware and phishing URLs…

Thread 🧵👇🏻 — Rapid (@Rapid_API)

Connecting things physically, mechanically or digitally can have profound effects. Here’s a list of 5 connectors that changed the world.

NoCode API is a great place to experiment with APIs and interact with them, without the need to setup servers and infrastructures. It gets the work done, reliable.

A Ruby interface to the Twitter API.

You might be wondering what on earth I am talking about but this is something I see API developers getting confused about regularly.

n8n is a free and source-available workflow automation tool

Mouser has solutions to increase productivity, reduce manual data entry and optimize time generating POs with our Electronic Order Automation Services.

DigiKey offers a complete set of APIs to share information and automate the ordering process.

Building a product that connects to multiple third-party products is a common approach — an annotated twitter thread exploring strategic…

OverAPI.com is a site collecting all the cheatsheets,all!

The five types of advertising apologies, explained.

Businesses are bound to make mistakes and disappoint their customers. But how you build your apology message and your careful attention to executing it appropriately can make the difference between losing those customers or increasing their loyalty. When delivered well, your apology message can improve the customer relationship to the point where it is stronger than if the mistake had never happened — a phenomenon known as the service recovery paradox. In this article, the author outlines five steps for writing an effective apology message, and explains why it’s important to share the apology process internally and with external stakeholders. It not only shows vulnerability from the organization, but also shows other customers that the company can be relied upon in times of distress.

In the span of five days, Saturday Night Live hired and fired comedian Shane Gillis after his use of sexist, homophobic, racist language— including

Three questions to ask during and after a heated controversy

Advice from therapists, religious leaders and people who suffered terrible wrongs on ways to find repentance and resolution.

No more excuses for bad apologies.

Learn how to use Python's Apriori algorithm to find frequent itemsets in transaction data automatically.

Uncovering the secret behind why breads are always conveniently placed beside butter in groceries

Explanation and examples of frequent itemset mining and association rule learning over relational databases in Python

Have you ever wondered how often do you buy certain items together? Why do you buy some items together? How likely do you purchase an item…

This article is about Market Basket Analysis & the Apriori algorithm that works behind it.

And why you will never get Taylor Swift tickets at face value

The tons of contraband lunch meat seized at the U.S.-Mexico border tell us something about the market value of nostalgia.

When the pandemic presented a buy-low opportunity, one college dropout hit the road and filled his truck with $200,000 worth of kicks.

The history of archeological discovery is riddled with forgeries. Discover three famous archeological hoaxes and the lessons they teach us about discovery and deception.

Explore the ancient village of Skara Brae, its connections to Skaill House, its haunting stories, and the mysteries surrounding its preservation and abandonment.

The world’s largest rainforest was long considered a virgin wilderness, but recent discoveries are challenging this view.

The story of the eruption of Mount Vesuvius is no longer one of annihilation; it also includes the people who managed to escape the city.

Dan Wheeler spent ten years sleeping in tents on his riverfront property before building anything permanent. The software engineer bought the land along Washington's Wenatchee River in 2010, drawn by years of rafting trips with friends through the area's rushing waters. Every camping trip reinforced what he already knew: this spot needed something, but only

Explore Design Milk’s 10 most captivating architecture projects of 2025, from micro-studios and floating homes to serene lakeside retreats.

Architectural copies of lost structures require reckoning with history and heritage. At what cost is the past rebuilt?

These six restored historic buildings are sending us.

Heat pump online training let you know the main types of pump in order to explain the thermal balance in housings and heating installations.

Camden Yards, which opened 30 years ago this summer, is revered for its design and downtown location. But its influence—along with its lessons—extends beyond architecture.

Buildings must be built to the requirements of the building code, a set of laws that governs how a building must be built.

From ancient Egypt to the Persian Empire, an ingenious method of catching the breeze kept people cool for millennia. Now, it could come to our aid once again.

From refrigerators to cars to Air Force One, Raymond Loewy's distinctive "cleanlining" sold products

Guests are transforming the sleepy town into a major destination for tourists seeking the "real Japan."

Embrace pre-fabricated, adaptable homes! Growing inequity, out-of-reach housing prices, and the speed of innovation in energy efficiency and technology demand it.

Sophists like Protagoras used the rhetoric of antilogic to escape from the illusion of truth and make room for uncertainty

Arguing well isn’t just about winning. A philosophical approach will help you and the other person get much more out of it

As someone who researches American religion, I find myself in impassioned conversations quite often. Religion is a beautiful element that…

(Cross posted to LessWrong)

How to turn arguments from vicious battles into productive dialogues.

How do you change someone’s mind if you think you are right and they are wrong? Psychology reveals the last thing to do is the tactic we usually resort to. You are, I’m afraid to say, mistake…

Stop wielding your values as a weapon and start offering them as a gift.

Imagine you could talk to Hieronymus Bosch, the authors of the Book of Revelation, or of the Voynich Manuscript—a bizarre 15th century text written in an uncrackable code; that you could solve centuries-old mysteries by asking them, “what were you thinking?” You might be disappointed to hear them say, as does Luigi Serafini, author and illustrator of the Codex Seraphinianus, “At the end of the day [it’s] similar to the Rorschach inkblot test.

This piece is print #4 in our Road Trip Attractions Series - a collection inspired by the interesting and quirky establishments you'll see billboards for on a road trip out west. This print is the billboard for the House of Weird - A Museum of Oddities & Unexplainables. We'd tell you what you might see in this mysterious pit stop, but it's just something you'd have to see to believe!

archived 21 Nov 2025 11:02:52 UTC

I was sixteen when my mother gifted me a painting by Ernie Barnes. I’d seen one Barnes painting at that point on the cover of Marvin Gaye’s 1976 album, I Want You, on the brown carpeted floor of my Auntie Sue’s apartment. Then I saw it five days a week for at least a decade during […]

Mysterious late-night visits, an undercover hunt for Hitler's horses, and a Picasso on the couch are business as usual for the Dutch sleuth.

The 'Social Register' was a who’s who of America’s rich and powerful—the heirs of robber barons, scions of political dynasties, and descendants of 'Mayflower' passengers. It was also the perfect hit list for the country’s hardest-working art thief.

The long read: Between 2022 and 2023, as many as 170 rare and valuable editions of Russian classics were stolen from libraries across Europe. Were the thieves merely low-level opportunists, or were bigger forces at work?

What is Lapis Lazuli? What are its origins? How has it persisted throughout the history of art?

Famous Fantastic Mysteries was a U.S. pulp magazine that specialized in reprinting classic tales of science fiction, fantasy, and adventure. It debuted in 1939 under the Munsey Company, already known for popular titles like Argosy, and quickly gained a devoted audience. The magazine revived olde

Chris Ware on the New Yorker artist, who contributed dozens of covers about the wealthy Peabody family and their housemaid, Fay.

Patrick Drahi made a fortune through debt-fuelled telecommunications companies, Sam Knight writes. Now he’s bringing his methods to the art market.

The snail may leave a trail of slime behind him, but a little slime will do a man no harm... whilst if you dance with dragons, you must expect to burn. - George R. R. Martin, The Mystery Knight As any Game of Thrones fan knows, being a knight has its downsides.

A common source of confusion that I experience when posting my artwork on social media is: _why?_ Why use a plotter when you could use a printer? It's slower. Less exact. More expensive. It fails, far too often. Inkjet printers became ubiquitous in the 1980s because they solved nearly all of these problems. So why are artists obsessed with pen plotters?

Storing an art collection properly is crucial for protecting and preserving the value of your artworks.

Keep your art safe by using professional art shippers, climate-controlled storage, and the right insurance to protect your art collection.

This series covers the core parts of the art market.

Discover how art auctions work by learning how to consign art, understand pricing, navigating key terms used by auction houses.

Fine art print using water-based inks on sustainably sourced cotton mix archival paper. • Available in multiple sizes • Trimmed with a 2cm / 1" border for framing • Available framed in white, black, and oak wooden frames

It would be a worthwhile exercise for any of us to sit down and attempt to draw up a list of our 100 favorite paintings of all time. Naturally, those not professionally involved with art history may have some trouble quite hitting that number.

This dreamy print entitled "Marfa Lights" is print #3 of 11 in our series by Bryan Peterson. Peterson's whimsical style is on full display in this beautiful print that captures the small town West Texas town of Marfa on a starry desert night.

Market value and establishing authenticity depend on uncovering an artwork’s past, which requires skilled provenance research.

Galleries are crucial touchpoints for discovering new artists and artworks. Here’s what you need to know about how to approach them.

Coming to Pueblo, CO, this fall, the Leonardo da Vinci Museum of North America will be the first and only museum of its kind in the continent.

Jennifer Dunn, the artist behind the Instagram account Mossy Hollow, characterizes her work as "Watercolor meme art," a distinctive blend of pop culture referen

To celebrate Rafael Araujo's talent and vision, I have curated a selection of his most stunning illustrations, showcasing the elegance and intricacy of his work.

Renaissance paintings, medieval archives, cloistered orchards—how one Italian scientist is uncovering secrets that could help combat a growing agricultural crisis

Walter Schnackenberg was born in 1880 in Lauterberg, Germany, and became a prominent painter and illustrator. At the age of 19, he moved to Munich to study art, first under Heinrich Knirr and then Franz von Stuck, both influential figures in the German art scene. His early work earned him recogn

From flipping to white glove sales, here are terms to know before you attend an auction.

During the Renaissance period, hands were as important a focus of attention as the face was, because they were the only other visible area of the body. Hence, representation of the position of the hands became a decorative element that was almost as important ...

Welcome to the "Auntieverse" — a surreal tribute to "auntie culture" by artist Niceaunties, inspired by the spirit of the women who care for each other and their families. From sushi-bedecked cars with legs to hot tub baths full of ramen, Niceaunties shares a visual feast that fuses AI and imagination and celebrates the eccentric, vibrant world of aunties with reverence and awe. (Slides created with AI including Midjourney and DALL·E 3 for text-to-image creation; magnific.ai and Topaz Labs for upscaling the images; Pikalabs and Runwayml for animation.)

Valery Slauk, a celebrated Belarusian artist, specializes in book art and easel graphics, particularly employing the etching technique. His work delves into Slavic mythology, crafting captivating worlds that blend literary inspiration with boundless imagination. With a deft balance between reali

German-American artist Henry Jerome Schile was born in Oberharmersbach, Baden-Württemberg, in 1829. He emigrated to the US in 1851 and worked in New York in the middle of the 19th century. h/t: vintag.es Henry Schile’s work is described by Harry T. Peters in America on Stone as: “Though of

After 34 years, not one of the 13 works stolen during the largest art theft in history has surfaced but the puzzling peculiarities of the case still draw interest.

Consuming culture gives us the emotional knowledge that can make us better people.

Discover the secrets behind Edward Hopper’s most iconic and enigmatic works. See how his marriage to artist Josephine Hopper shaped his art.

Sophie Walter, Assistant Curator at London Fire Brigade Museum, on the small, beautiful and potentially fatal Glass Fire Grenade When they were first introduced in the nineteenth century, Glass Fire Grenades were produced as decorative glass bottles with a bulbous...

Europe at the end of the nineteenth century and beginning of the twentieth: what a time and place to be alive.

The dealer has been so successful selling art to masters of the universe that he has become one of them.

A new show at London's Courtauld Gallery will explore the value of counterfeit art

For more than thirty years, Ed Binkley has been producing stunning fantasy artwork. His exceptional creations have been showcased in a multitude of publications and he has partnered with esteemed entities such as Lucasfilm, ImagineFX, Wizards of the Coast, and Artifacts Puzzles, among others.

Advice from the world's greatest art thief

After a painting by the Dutch artist sold at auction, a movie producer claimed to be the owner. It later vanished from sight, with a trail leading to Caribbean tax havens and a jailed Chinese billionaire.

Tomb raiders, crooked art dealers, and museum curators fed billionaire Michael Steinhardt’s addiction to antiquities. Many also happened to be stolen.

Intricate designs painted by biscuit artist Ella Hawkins are part of a lengthy baking tradition

After his brother’s death, Patrick Bringley took a job at the grandest place he could find.

The goal is not to expose the “slipups” of the masters but to understand the human brain.

The long read: In 2016, artist César Aréchiga talked one of Mexico’s most dangerous maximum security prisons into letting him run art classes for its inmates, many of them violent gang members. Could he really change their lives?

Wolfgang and Helene Beltracchi’s forgeries infiltrated museums, auction houses and private collections. A decade after their conviction, psychoanalyst Jeannette Fischer asks: Why did they do it?

For lots of rock-poster collectors, even those who like to think they’re in the know, a common question is, “Who’s Luke Martin?”

A billionaire playboy’s alleged murder is at the center of the world’s most confounding heist job.

On his way to becoming an international icon, the subversive and secretive street artist turned the art world upside-down

A collector thought he had bought a painting by the celebrated British artist. How far would he go to prove it?

Andres Valencia’s paintings have sold for more than $125,000. And he’s 10 years old.

Auction houses and galleries are getting creative, partnering to drive demand and give their clients access to the best works.

The stolen masterpieces have never turned up—and nobody’s really looking for them

Did the artist paint a security camera (or a condom, or a portrait of rigatoni) into “The Red Studio”? An investigation at MoMA looks for clues.

You can't make this shit up

How Banksy created a private key art authentication system with forged ten pound bank notes ripped in half.

The Antico Setificio Fiorentino, which relies on looms from the 18th and 19th centuries, has been producing precious textiles since 1786.

We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation. It comprises 60,000 images of artwork from 10...

Polish illustrator and graphic designer Tomasz Majewski combines traditional techniques with digital work to produce cool pop culture creations. More: Instagram, Behance

Out of this world artworks by Michał Klimczak, a graphic designer and concept artist based in Krakow, Poland. More: Instagram, Behance

The Svaneti Museum of History and Ethnography in Georgia is home to one of the world’s great collections of medieval Christian art, writes William Dunbar

Driven by buyers' need for consistency and explanation, the most popular pricing method uses a surprisingly simple formula based on size.

The colour violet was largely missing from art before the Impressionists, and is seen differently by different cultures. Why?

National Gallery of Art

Browse and download high-resolution, public domain Paintings, Drawings, Illustrations and Posters.

When nearly $3.5M of rare books were stolen in an audacious heist at Feltham in 2017, police wondered, what’s the story?

The Collections database consists of entries for more than 480,000 works in the Musée du Louvre and Musée National Eugène-Delacroix.

Western museums are under pressure to return looted treasure, but what of those in private collections?

What are the greatest art heists of all time? See a list of the 25 most memorable thefts from museums.

In October 2020, Miami-based art collector Pablo Rodriguez-Fraile spent almost $67,000 on a 10-second video artwork that he could have watched for free online. Last week, he sold it for $6.6 million.

Buy art from the world's largest community of independent artists and iconic brands. Shop for wall art, home decor, iPhone cases, and more!

How a dozen possibly fraudulent and forged Indigenous artworks left Texas and ended up on museum walls in Wyoming.

Usage of the new model, with examples and Colab Notebook.

Forgeries have become so good – and so costly – that Sotheby’s has brought in its own in-house fraud-busting expert.

First trips to Paris all run the same risk: that of the museums consuming all of one's time in the city. What those new to Paris need is a museum-going strategy, not that one size will fit all.

What is neuroscience doing to art?

Five months on we look at the steps and measurements implemented by experts to start rebuilding the fire-ravaged cathedral

A Dutch gallerist made thousands of forgeries and passed them off as the work of real artists. When he was caught, a new con began.

Two decades after Rudy Giuliani tried to rid New York City of graffiti, the art form is flourishing—with unexpected consequences.

How times have changed since our late 80s college days. Undergrads do research online, upload assignments to a server, stream music, download affirmative sexual consent contracts, and turn to Facebook when it's time to find a ride home for the holidays.

The author shows how new mathematical techniques can be used to revitalize a 650-year-old work of art.

Art historian Arthur Brand managed to track down the 1983 painting Buste de Femme (Dora Maar), which went missing from a Saudi prince’s boat in 1999.

Some scientists believe that the earliest humans were actually colorblind, and had no concept of the color blue.

The skilled climber and thief Vjeran Tomic, whom the French press referred to as Spider-Man, has described robbery as an act of imagination.

Emergence is the story of natural laws and processes, their inherent beauty, and their action to yield the universe, us and the world we live in.

The Art Institute of Chicago recently unveiled a new website design. As part of their first design upgrade in 6 years, they have placed more than 52,000 high-resolution images from their collection online, available to all comers without restr

Is the Chinese government behind one of the boldest art-crime waves in history?

I used to think Marfa was a kind of practical joke that West Texans were playing on cultural elites. It’s remote even for Texas. The nearest airports are in El Paso and Carlsbad, New Mexico, each 2…

You just can't see what it's become.

In June, I shared a bonus article with my curated and bookmarked research paper lists to the paid subscribers who make this Substack possible.

A curated list of LLM research papers from July–December 2025, organized by reasoning models, inference-time scaling, architectures, training efficiency, and...

Multisets are sets that allow repetition of elements. As such, multisets pave the way to a number of interesting possibilities of theoretical and applied nature. In the present work, after revising the main aspects of traditional sets, we introduce some of the main concepts and characteristics of multisets, followed by their generalization to take into account vectors and matrices. An approach is also proposed in which the real, negative multiplicities are allowed, implying the multiset universe to become finite and well-defined, corresponding to the multiset with null multiplicities. The complement operation in multisets is then defined, which allows properties involving complement -- including the De Morgan theorem -- to be recovered in multisets. In addition, it becomes possible to extend multisets to functions (which become multifunctions), scalar fields and other continuous mathematical structure, therefore achieving an enhanced space endowed with all algebraic operations plus set theoretical operations including union, intersection, and complementation. The possibility to define a set operation between mfunctions, namely the common product, that is analogous to the traditional inner product is also proposed, paving the way to obtaining respective mfunction transformations, and it is argued that the Walsh functions provide an orthogonal basis for the mfunctions space under the common product. This result also allowed the proposal of performing integrated signal processing operations on mset mfunctions, including filtering and enhanced template matching. Relationships between the cosine similarity index and the Jaccard index are also identified, including the presentation of an intersection-based variation of the cosine index. The potential of multisets in pattern recognition and deep learning is also briefly characterized and illustrated.

Compute-in-SRAM architectures offer a promising approach to achieving higher performance and energy efficiency across a range of data-intensive applications. However, prior evaluations have largely relied on simulators or small prototypes, limiting the understanding of their real-world potential. In this work, we present a comprehensive performance and energy characterization of a commercial compute-in-SRAM device, the GSI APU, under realistic workloads. We compare the GSI APU against established architectures, including CPUs and GPUs, to quantify its energy efficiency and performance potential. We introduce an analytical framework for general-purpose compute-in-SRAM devices that reveals fundamental optimization principles by modeling performance trade-offs, thereby guiding program optimizations. Exploiting the fine-grained parallelism of tightly integrated memory-compute architectures requires careful data management. We address this by proposing three optimizations: communication-aware reduction mapping, coalesced DMA, and broadcast-friendly data layouts. When applied to retrieval-augmented generation (RAG) over large corpora (10GB--200GB), these optimizations enable our compute-in-SRAM system to accelerate retrieval by 4.8$\times$--6.6$\times$ over an optimized CPU baseline, improving end-to-end RAG latency by 1.1$\times$--1.8$\times$. The shared off-chip memory bandwidth is modeled using a simulated HBM, while all other components are measured on the real compute-in-SRAM device. Critically, this system matches the performance of an NVIDIA A6000 GPU for RAG while being significantly more energy-efficient (54.4$\times$-117.9$\times$ reduction). These findings validate the viability of compute-in-SRAM for complex, real-world applications and provide guidance for advancing the technology.

The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods. Indeed, many high-dimensional learning tasks previously thought to be beyond reach -- such as computer vision, playing Go, or protein folding -- are in fact feasible with appropriate computational scale. Remarkably, the essence of deep learning is built from two simple algorithmic principles: first, the notion of representation or feature learning, whereby adapted, often hierarchical, features capture the appropriate notion of regularity for each task, and second, learning by local gradient-descent type methods, typically implemented as backpropagation. While learning generic functions in high dimensions is a cursed estimation problem, most tasks of interest are not generic, and come with essential pre-defined regularities arising from the underlying low-dimensionality and structure of the physical world. This text is concerned with exposing these regularities through unified geometric principles that can be applied throughout a wide spectrum of applications. Such a 'geometric unification' endeavour, in the spirit of Felix Klein's Erlangen Program, serves a dual purpose: on one hand, it provides a common mathematical framework to study the most successful neural network architectures, such as CNNs, RNNs, GNNs, and Transformers. On the other hand, it gives a constructive procedure to incorporate prior physical knowledge into neural architectures and provide principled way to build future architectures yet to be invented.

Memory latency, bandwidth, capacity, and energy increasingly limit performance. In this paper, we reconsider proposed system architectures that consist of huge (many-terabyte to petabyte scale) memories shared among large numbers of CPUs. We argue two practical engineering challenges, scaling and signaling, limit such designs. We propose the opposite approach. Rather than create large, shared, homogenous memories, systems explicitly break memory up into smaller slices more tightly coupled with compute elements. Leveraging advances in 2.5D/3D integration, this compute-memory node provisions private local memory, enabling accesses of node-exclusive data through micrometer-scale distances, and dramatically reduced access cost. In-package memory elements support shared state within a processor, providing far better bandwidth and energy-efficiency than DRAM, which is used as main memory for large working sets and cold data. Hardware making memory capacities and distances explicit allows software to efficiently compose this hierarchy, managing data placement and movement.

Reasoning, the process of devising and executing complex goal-oriented action sequences, remains a critical challenge in AI. Current large language models (LLMs) primarily employ Chain-of-Thought (CoT) techniques, which suffer from brittle task decomposition, extensive data requirements, and high latency. Inspired by the hierarchical and multi-timescale processing in the human brain, we propose the Hierarchical Reasoning Model (HRM), a novel recurrent architecture that attains significant computational depth while maintaining both training stability and efficiency. HRM executes sequential reasoning tasks in a single forward pass without explicit supervision of the intermediate process, through two interdependent recurrent modules: a high-level module responsible for slow, abstract planning, and a low-level module handling rapid, detailed computations. With only 27 million parameters, HRM achieves exceptional performance on complex reasoning tasks using only 1000 training samples. The model operates without pre-training or CoT data, yet achieves nearly perfect performance on challenging tasks including complex Sudoku puzzles and optimal path finding in large mazes. Furthermore, HRM outperforms much larger models with significantly longer context windows on the Abstraction and Reasoning Corpus (ARC), a key benchmark for measuring artificial general intelligence capabilities. These results underscore HRM's potential as a transformative advancement toward universal computation and general-purpose reasoning systems.