Reading Comprehension: How to Retain More of Every Book You Read

It's important to read books, but it's just as important to remember what you read. Read this article to learn three reading comprehension strategies.

Why Iceland’s Christmas Witch Is Much Cooler (and Scarier) Than Krampus

With roots dating back to the 13th century, Grýla is not to be messed with.

How To Make Starbucks-Style Cold Brew Coffee at Home

Everything you need to know for DIY big-Batch cold brew.

In a Pandemic Fairy Tale, a Garden Leads to a Magical Friendship (Published 2020)

A 4-year-old girl coping with the loneliness of the pandemic created a tiny garden, and kindled an unlikely friendship with an enchanted neighbor who moved into her tree.

Gallery / D3 / Observable

Looking for a good D3 example? Here’s a few (okay, …) to peruse. Animation D3’s data join, interpolators, and easings enable flexible animated transitions between views while preserving object constancy. Interaction D3’s low-level approach allows for performant incremental…

KMP Algorithm (String Matching) Demystified

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…

BFGS in a Nutshell: An Introduction to Quasi-Newton Methods

Demystifying the inner workings of BFGS optimization

Lagrange multipliers with visualizations and code | by Rohit Pandey | Towar

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…

Semiconductor Assembly Glossary

Strange Company

A walk on the weird side of history

Beyond One-Hot. 17 Ways of Transforming Categorical Features Into Numeric F

All the encodings that are worth knowing — from OrdinalEncoder to CatBoostEncoder — explained and coded from scratch in Python

Particle Swarm Optimization Visually Explained

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

Browse the State-of-the-Art in Machine Learning | Papers With Code

**Pose Estimation** is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation. A common…

Computer Vision | Papers With Code

Dimensionality reduction is the task of reducing the dimensionality of a dataset. ( Image credit: [openTSNE](https://github.com/pavlin-policar/openTSNE) )

Top 10 Python libraries of 2020 you should know about | Tryolabs Blog

There are so many amazing Python libraries out there that it's hard to keep track of all of them. That's why we share with you our hand-picked selection of some top libraries.

Top Product Management and UX Articles of 2020

These were my favorite product management and UX articles of 2020, which is the 5th year I’ve compiled this list. Though 2020 was a…

People AI Guidebook | PAIR

A toolkit for teams building human-centered AI products.

Methodology | Papers With Code

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Methodology | Papers With Code

**Transfer Learning** is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related…

Methodology | Papers With Code

**Representation Learning** is a process in machine learning where algorithms extract meaningful patterns from raw data to create representations that are easier to understand and process. These representations can be designed for interpretability, reveal hidden features, or be…

Browse the State-of-the-Art in Machine Learning | Papers With Code

**Sentiment Analysis** is the task of classifying the polarity of a given text. For instance, a text-based tweet can be categorized into either "positive", "negative", or "neutral". Given the text and accompanying labels, a model can be trained to predict the correct sentiment…

Object Tracking | Papers With Code

**Object tracking** is the task of taking an initial set of object detections, creating a unique ID for each of the initial detections, and then tracking each of the objects as they move around frames in a video, maintaining the ID assignment. State-of-the-art methods involve…

Computer Vision | Papers With Code

**Image Retrieval** is a fundamental and long-standing computer vision task that involves finding images similar to a provided query from a large database. It's often considered as a form of fine-grained, instance-level classification. Not just integral to image recognition…

Computer Vision | Papers With Code

**Zero-shot learning (ZSL)** is a model's ability to detect classes never seen during training. The condition is that the classes are not known during supervised learning. Earlier work in zero-shot learning use attributes in a two-step approach to infer unknown classes. In the…

Computer Vision | Papers With Code

**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…

Computer Vision | Papers With Code

**Few-Shot Learning** is an example of meta-learning, where a learner is trained on several related tasks, during the meta-training phase, so that it can generalize well to unseen (but related) tasks with just few examples, during the meta-testing phase. An effective approach to…

Computer Vision | Papers With Code

**Depth Estimation** is the task of measuring the distance of each pixel relative to the camera. Depth is extracted from either monocular (single) or stereo (multiple views of a scene) images. Traditional methods use multi-view geometry to find the relationship between the…

Computer Vision | Papers With Code

**Facial Recognition** is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those…

Computer Vision | Papers With Code

**Action Recognition** is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes. In the video domain, it is an open…

Computer Vision | Papers With Code

**Denoising** is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of…

Computer Vision | Papers With Code

**Super-Resolution** is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while…

Computer Vision | Papers With Code

Autonomous driving is the task of driving a vehicle without human conduction. Many of the state-of-the-art results can be found at more general task pages such as [3D Object Detection](https://paperswithcode.com/task/3d-object-detection) and [Semantic…

Computer Vision | Papers With Code

Data augmentation involves techniques used for increasing the amount of data, based on different modifications, to expand the amount of examples in the original dataset. Data augmentation not only helps to grow the dataset but it also increases the diversity of the dataset. When…

Computer Vision | Papers With Code

**Domain Adaptation** is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized…

Browse the State-of-the-Art in Machine Learning | Papers With Code

**Image Generation** (synthesis) is the task of generating new images from an existing dataset. - **Unconditional generation** refers to generating samples unconditionally from the dataset, i.e. $p(y)$ - **[Conditional image generation](/task/conditional-image-generation)**…

Browse the State-of-the-Art in Machine Learning | Papers With Code

**Object Detection** is a computer vision task in which the goal is to detect and locate objects of interest in an image or video. The task involves identifying the position and boundaries of objects in an image, and classifying the objects into different categories. It forms a…

Browse the State-of-the-Art in Machine Learning | Papers With Code

**Image Classification** is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike [object detection](/task/object-detection), which involves classification and location of multiple objects within an…

Browse the State-of-the-Art in Machine Learning | Papers With Code

**Semantic Segmentation** is a computer vision task in which the goal is to categorize each pixel in an image into a class or object. The goal is to produce a dense pixel-wise segmentation map of an image, where each pixel is assigned to a specific class or object. Some example…

Mythic Case Study

How Mythic got its optimized domain-specific core without compromises or delays.

"If it Hadn't Been for the Prompt Work of the Medics": FSB Officer Inadvertently Confesses Murder Plot to Navalny - bellingcat

Bellingcat and its partners reported that Russia’s Federal Security Service (FSB) was implicated in the near-fatal nerve-agent poisoning of Alexey Navalny on 20 August 2020. The report identified eight clandestine operatives with medical and chemical/biological warfare expertise…

The Fall Of Mic Was A Warning | HuffPost

"I don’t need a pair of Nikes. I need a 401(k)" -- and other lessons from the death of a venture-backed, Facebook-dependent, millennial-focused news site.

Everything Product People Need to Know About Transformers, GPT-3, and Huggi

Or, How to Act Like You Know About the Biggest AI Development since CNNs

How to Overcome 5 Common B2B Sales Challenges

Generating and retaining business customers makes you deal with longer (and more complicated) sales cycles, more demanding customers, and huge amounts of data.

Enneagram of Personality

The Enneagram of Personality, or simply the Enneagram, is a pseudoscientific model of the human psyche which is principally understood and taught as a typology of nine interconnected personality types.

L-System

An L-system or Lindenmayer system is a parallel rewriting system and a type of formal grammar. An L-system consists of an alphabet of symbols that can be used to make strings, a collection of production rules that expand each symbol into some larger string of symbols, an initial…

Earth on Nautilus: The Strange Blissfulness of Storms

You Are Solving The Wrong Problem | UX Magazine

When solving a difficult problem, re-ask the problem so the solution helps you learn faster.

Paperspace | Gradient Projects

Build and scale ML applications with a cloud platform focused on speed and simplicity.

A Chicken Dish That Makes It Feel Like Christmas (Published 2020)

When Nik Sharma left Mumbai for Ohio years ago, he had to leave his family’s holiday celebration behind too. Now he recreates one of his favorite dishes, chicken cafreal, in his own kitchen.

Kurt Vonnegut on the 8 "shapes" of stories

Before fame, Kurt Vonnegut wrote a master's thesis on the shapes of stories for the anthropology department at the University of Chicago.