Popular GitHub Repositories for Game Optimization

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

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

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

A game theoretic approach to explain the output of any machine learning model.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

A hyperparameter optimization framework

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

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

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Fast and Accurate ML in 3 Lines of Code

? An exciting game of programming and Artificial Intelligence

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 15+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Automated Machine Learning with scikit-learn

Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

Transformer related optimization, including BERT, GPT

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.