Open source. Open possibilities.

SANA is NVIDIA's open-source family of efficient diffusion models for high-resolution image and video generation, with training and inference code, linear attention, DC-AE compression and 4-bit deployment.

Stable Baselines3 (SB3) is a set of reliable PyTorch implementations of reinforcement learning algorithms designed for research and industry replication.

Collection of simple PyTorch implementations of neural networks and deep learning papers with documented side-by-side explanations, covering transformers, GANs, diffusion models, RL, optimizers, and more.

Jericho is a lightweight Python interface connecting learning agents to man-made Interactive Fiction games, featuring Frotz emulation, stochastic environments, and comprehensive documentation for AI research.

Free, open-source AI engineering curriculum from first principles: 523 lessons in 20 phases (~342 hours), with math-to-production coverage in Python, TypeScript, Rust, and Julia. Every lesson ships a reusable prompt, skill, agent, or MCP server; includes an installable AI tutor and Claude certification prep.

Unsloth is a desktop application and framework for running and training large language models (LLMs) and diffusion models locally across Windows, macOS, and Linux.

A collection of machine learning and deep learning code examples and tutorials accompanying online courses. Covers topics from linear regression to reinforcement learning, NLP, computer vision, and generative AI.

Unity ML-Agents Toolkit is an open-source framework that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning, with PyTorch-based implementations.

Adrastea is a Python dual-engine system that pairs a deterministic task execution core (Alpha) with a probabilistic reasoning engine (Beta) for autonomous orchestration: Alpha schedules and runs local programs with reinforcement-learning planning and local Ollama inference, while Beta monitors telemetry, resolves anomalies, tunes scoring weights, and can consult frontier LLMs via MCP.

Ray is a unified framework for scaling AI and Python applications from a single laptop to a distributed cluster.

Reinforcement learning library for operational decisions—pricing, inventory, energy, queues, supply chains. 31 algorithms with typed interfaces, classical baselines, and reproducible benchmarks.

SGLang is a high-performance serving framework for large language models (LLMs) and multimodal models, designed for low-latency and high-throughput inference.

Reinfors is a high-throughput reinforcement-learning library that runs game dynamics, search, and episode orchestration in parallel Rust, while keeping Python-based networks and training entirely under the caller's control.

A curated list of computer science courses with video lectures, covering algorithms, AI, databases, operating systems, and more.