Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.
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Learn AI Engineering! Learn it. Build it. Ship it for others.
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.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Accelerated deep learning R&D
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Maze Applied Reinforcement Learning Framework
Free Course : Data, Machine Learning, Deep Learning and AI Engineering, the long way round: the math, the code, the systems and the security. 173 lessons, 166 runnable labs, no shortcuts. Free under CC BY-NC 4.0.