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ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
MLX: An array framework for Apple silicon
Cross-platform, customizable ML solutions for live and streaming media.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
A gallery that showcases on-device ML/GenAI use cases and allows people to try and use models locally.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Minimalist ML framework for Rust
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
LiteRT, successor to TensorFlow Lite. is Google's On-device framework for high-performance ML & GenAI deployment on edge platforms, via efficient conversion, runtime, and optimization
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
Universal LLM Deployment Engine with ML Compilation
A machine learning compiler for GPUs, CPUs, and ML accelerators
Fast and Accurate ML in 3 Lines of Code
Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
LightlyStudio - The Unified Data Platform for Multimodal ML
A Flexible and Powerful Parameter Server for large-scale machine learning
A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.
A collection of sample apps to demonstrate how to use Google's ML Kit APIs on Android and iOS
Interactive, source-linked ML workflow diagrams written by your coding assistant (Copilot, Codex or Claude Code) and opened in VS Code.
Live AI and machine learning internships for students, refreshed through the Zapply job pipeline.
Core ML model zoo for iOS/macOS — PyTorch models converted to ready-to-use .mlpackage, each with a conversion script and SwiftUI sample app. Sibling repos cover Apple's Core AI framework (iOS/macOS 27) and on-device LLMs.
LLMs and VLMs with MLX Swift
⚡ Fastest way to serve open source ML models to millions
Examples using MLX Swift
Tiny post-quantum encryption for sensitive data. Write-only by design. ML-KEM-768 + X25519 + AES-256-GCM. Please break it.