Topic Modeling with LDA Introduction
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.
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What is the tidyverse? · R Views
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…
Deep Reinforcement Learning Demystified (Episode 0)
I recently became interested in learning more about deep reinforcement learning. Recently, big news headlines were made as deep…
SQLite small blob storage: 35% Faster Than the Filesystem
Intuitive Understanding of Word Embeddings: Count Vectors to Word2Vec
Word embeddings are techniques used in natural language processing. This includes tools & techniques like word2vec, TD-IDF, count vectors, etc. Explore Now!
Word2Vec (skip-gram model): PART 1 - Intuition.
Most of the content here is from Chris’s blog. I have condensed it and made minor adaptations.
Operations Research with R
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…
Top 50 ggplot2 Visualizations - The Master List (With Full R Code)
R Language Tutorials for Advanced Statistics
Boost.Hana: User Manual
Assessing Data with Item Response Theory
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.
Train your deep model faster and sharper — two novel techniques
How to Handle Imbalanced Classes in Machine Learning
Imbalanced classes put "accuracy" out of business. This is a surprisingly common problem in machine learning, and this guide shows you how to handle it.
Using word embedding to enable semantic queries on relational databases
Counting Bloom Filter in C – Tony Allen – Medium
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…
Reducing dimensionality from dimensionality reduction techniques
In this post I will do my best to demystify three dimensionality reduction techniques; PCA, t-SNE and Auto Encoders. My main motivation for…
Kimbra Climbs To The 'Top Of The World' In New Single : NPR
With angry synths, religious imagery and a symbolic music video, the New Zealand singer provides the empowering song we need at this time of year.
arbox/data-science-with-ruby: Practical Data Science with Ruby based tools.
Practical Data Science with Ruby based tools.
6 Deep Learning Techniques They Never Taught You In School
They can really help you
A practical explanation of a Naive Bayes classifier
Medallia's text analytics software tool provides actionable insights via customer and employee experience sentiment data analysis from reviews & comments.
https://blog.openai.com/openai-baselines-ppo/
Ten Things A Serious JavaScript Developer Should Learn
There’s been an interesting Reddit thread circling my corner of the internet for the last week or so. It started with a question: I’m inviting pure opinion here, but what’s your list of ten things that everyone looking for a good javascript role should know and understand…
https://news.21.co/quantifying-decentralization-e39db233c28e
machine learning benchmarks - Google Search
[D] A Comparison of Six Methods for Missing Data Imputation
2.9M subscribers in the MachineLearning community. Beginners -> /r/mlquestions , AGI -> /r/singularity, career advices -> /r/cscareerquestions…
Metaprogramming: Writing in Ruby with... Ruby | Toptal
Ruby metaprogramming, one of the most interesting aspects of Ruby, enables the programming language to achieve an extreme level of expressiveness. It is because of this very feature that many gems, such as RSpec and ActiveRecord, can work the way they do. In this article, Toptal…
Mental Models I Find Repeatedly Useful — Medium
2019 UPDATE: Since this post came out, I co-authored a book about it called Super Thinking: The Big Book of Mental Models.
The Beauty of Bresenham's Algorithm
Batching – A powerful way to solve N 1 queries every Rubyist should know
In this post I’m going to tell you about batching as a technique to help avoid N+1 queries, existing battle-tested tools like Haskell Haxl…
Understanding a fundamental Ruby abstraction for concurrency | via @codeshi
In this post
Martinosis Blog
Removing Outliers Using Standard Deviation in Python
Standard Deviation is one of the most underrated statistical tools out there. It’s an extremely useful metric that most people know how to calculate but very few know how to use effectively.
An Intuitive Guide to Deep Network Architectures
How and why do different Deep Learning models work? We provide an intuitive explanation for 3 very popular DL models: Resnet, Inception, and Xception.
Support Vector Machine (SVM) Tutorial: Learning SVMs From Examples
In this post, we will try to gain a high-level understanding of how SVMs work. I’ll focus on developing intuition rather than rigor. What that essentially means is we will skip as much of the math as possible and develop a strong intuition of the working principle.
An Introduction to the Fast Fourier Transform
This article will review the basics of the decimation-in-time FFT algorithms.
Gentle Introduction to Generative Long Short-Term Memory Networks - MachineLearningMastery.com
The Long Short-Term Memory recurrent neural network was developed for sequence prediction. In addition to sequence prediction problems. LSTMs can also be used as a generative model In this post, you will discover how LSTMs can be used as generative models. After completing this…
lect04_LEF.pdf
Layered Data Visualizations Using R, Plotly, and Displayr
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...
React Crash Course for Beginners, Part 1
In this tutorial series we'll dive right into using React as we build a fully working app to display a gallery of movies. Learning how to build an app from scratch is a great opportunity to...
An introduction to Vue.js - Chapter 1 - Basic Setup
This is a simple introduction to Vue.js, starting with a simple setup
An introduction to Vue.js - Chapter 2 - Components (Part I)
This is a simple introduction to Vue.js, this time with simple components
Numba: High-Performance Python with CUDA Acceleration
Numba is an open-source Python compiler from Anaconda that can compile Python code for high-performance execution on CUDA-capable GPUs or multicore CPUs.
Parallel processing with Unix tools
Tools for multi-processing on unix
Using Google Analytics with Angular
Marketing Multi-Channel Attribution model based on Sales Funnel with R
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
Understanding Args and Kwargs in Python
In this tutorial, I will be focusing on arguments (*args) and keyword arguments (*kwargs) in Python. I will teach you what args and kwargs are and, most importantly, how to use them—that is...
Seven Things You Might Not Know About Numba | Parallel Forall
1.3M subscribers in the Python community. The official Python community for Reddit! Stay up to date with the latest news, packages, and meta…
Understanding Machine Learning 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.
Your Guide to Master Hypothesis Testing in Statistics - DataScienceCentral.com
This article was written by Sunil Ray. Sunil is a Business Analytics and Intelligence professional with deep experience. Introduction – the difference in mindset I started my career as a MIS professional and then made my way into Business Intelligence (BI) followed by Business…
vestuto/reusable-python: A tutorial on organizing python code into reusable
A tutorial on organizing python code into reusable units, building packages, and using conda. - vestuto/reusable-python
Image Convolution in R using Magick
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…