Google Research

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

FinRL®: Financial Reinforcement Learning. 🔥

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

Code samples used on cloud.google.com

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Book about interpretable machine learning

Repo for the Deep Reinforcement Learning Nanodegree program

A collection of infrastructure and tools for research in neural network interpretability.

A small package to create visualizations of PyTorch execution graphs

Productivity Tools for Plotly + Pandas

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

Fast, general, and tested differentiable structured prediction in PyTorch

Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai

A benchmark environment for fully cooperative human-AI performance.

[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.

The repository is for safe reinforcement learning baselines.

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

Maximum Entropy and Maximum Causal Entropy Inverse Reinforcement Learning Implementation in Python

for code created as part of http://studywolf.wordpress.com

[Coursera] Reinforcement Learning Specialization by "University of Alberta" & "Alberta Machine Intelligence Institute"

Oriented FAST and Rotated BRIEF using opencv

Shared autonomy via deep reinforcement learning

Exploring Bayesian Optimization

Labs for understanding and coding Standard Reinforcement Learning concepts

Machine Learning for Audio Signals in Python

Deep PILCO PyTorch Implementation