Popular GitHub Repositories for Combining Imitation Reinforcement

??? 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.

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

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.

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.

An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language models. The goal of this repo is to provide the simplest implementation of a deep research agent - e.g. an agent that can refine its research direction overtime and deep dive into a topic.

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.

DeerFlow is a community-driven Deep Research framework, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.

Machine learning, in numpy

Python Implementation of Reinforcement Learning: An Introduction

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

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

FinRL: Financial Reinforcement Learning. ?

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.

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

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

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