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 7 complete days
24 repositories by Attention Score · Oct 27, 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.
Open, source-backed catalog of computer-use agents: reviewed papers, GUI models, datasets, benchmarks, tools, and reusable JSONL/SQLite data.
SGLang is a high-performance serving framework for large language models and multimodal models.
Infrastructure for continually self‑improving agents
The absolute trainer to light up AI agents.
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 standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
🧑🏫 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, ... 🧠
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.
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
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)
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!
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
Python Implementation of Reinforcement Learning: An Introduction
A collection of environments for autonomous driving and tactical decision-making tasks
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
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