1.rohitg00 / ai-engineering-from-scratch
Learn AI Engineering! Learn it. Build it. Ship it for others.
Ranked by Attention Score: stars gained over the last 180 complete days
40 repositories by Attention Score · May 7, 2026 – Nov 2, 2026 (UTC)
Learn AI Engineering! Learn it. Build it. Ship it for others.
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.
SGLang is a high-performance serving framework for large language models and multimodal models.
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
The absolute trainer to light up AI agents.
🧑🏫 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, ... 🧠
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
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 standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
PettingZoo and Gymnasium bindings for popular reinforcement learning environments outside of Farama
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Python Implementation of Reinforcement Learning: An Introduction
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
A library of reinforcement learning components and agents
A collection of environments for autonomous driving and tactical decision-making tasks
Machine learning, in numpy
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
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Trax — Deep Learning with Clear Code and Speed
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
[ICRA] Crowd-aware Robot Navigation
Accelerated deep learning R&D
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
A curated list of Monte Carlo tree search papers with implementations.
Deep Reinforcement Learning for Keras.
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Computational framework for reinforcement learning in traffic control
No description provided by the repository host.
Maze Applied Reinforcement Learning Framework
Scalable, event-driven, deep-learning-friendly backtesting library
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 ...