The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well a…

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning libr…

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

A toolkit for developing and comparing reinforcement learning algorithms.

a distributed Hyperband implementation on Steroids

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…

An implementation of the Augmented Random Search algorithm

ConvNet training using pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

The Leek group guide to data sharing

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.