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Data Science at Home is a podcast about machine learning, artificial intelligence, and algorithms.

Can you spot the DeepFake? Detect Fakes challenges you to discern AI-manipulated videos from real videos. Can you do better than an algorithm?

Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.

Graph layout algorithms in pure Julia.

Some experiments with the coordinate descent algorithm used in the (Sparse) Group Lasso model.

A library for developing and comparing reinforcement learning algorithms (successor of [gym])(https://github.com/openai/gym).

Implementation of the hdbscan algorithm in Python - used for clustering.

Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.

General Machine Learning library using Numenta’s Cortical Learning Algorithm.

Helps teams build, deploy, observe or operate machine-learning systems.

Objective-C version of Google Palette algorithm in Java.A tool to extract the main color of an image.

JavaScript implementation of the k nearest neighbors algorithm for supervised learning.

Just a simple implementation of K-Nearest Neighbors algorithm using with a bunch of similarity measures.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Introduction to machine learning covering basic theory, algorithms and applications.

Algorithms for learning and inference with discrete probabilistic models.

A Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback.

About helping professional programmers confidently apply machine learning algorithms to address complex problems.

Open-source project that supports software development with code generation, analysis, debugging, or documentation.

Metric Learning Algorithms in Python.

A set of functions to support the development of machine learning algorithms.

Framework that implements AutoML algorithms for model architecture search at scale.

Algorithm capable of fully capturing the impact of data drift on performance.

An experimental physical interface for the NSynth machine learning algorithm.