Popular GitHub Repositories for Evolutionary Reinforcement Learinig

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Machine learning, in numpy

Python Implementation of Reinforcement Learning: An Introduction

FinRL: Financial Reinforcement Learning. ?

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

强化学习中文教程（蘑菇书?），在线阅读地址：https://datawhalechina.github.io/easy-rl/

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

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

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Tutorials, assignments, and competitions for MIT Deep Learning related courses.