Open source. Open possibilities.

Made With ML is an open-source course and codebase teaching how to design, develop, deploy and iterate on production-grade machine learning applications, covering MLOps, testing, serving, CI/CD and continual learning.

Colossal-AI is an open-source system for training and running large AI models more cheaply and efficiently, offering parallel training strategies, memory management, and inference acceleration for LLMs, diffusion models, and more.

PaddlePaddle is an industrial-grade deep learning platform providing a comprehensive framework for machine learning, including model libraries and development kits.

A comprehensive toolkit for computer vision that provides model-agnostic building blocks for data loading, visualization, and dataset management.

Gradio is an open-source Python library for quickly building and sharing web applications for machine learning models, APIs, or any Python function without requiring web development experience.

Magika is Google's AI-powered file content type detection tool. It uses a small deep learning model to identify 200+ file types in milliseconds on a single CPU, with ~99% accuracy. Available as a Rust CLI plus Python, JavaScript and Go bindings.

Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch, supporting universal probabilistic models and automated inference.

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.

Sonnet is a neural network library by DeepMind built on TensorFlow 2. It provides simple, composable abstractions via the snt.Module concept for machine learning research, supporting custom modules, serialization, and distributed training.

Tesseract.js is a JavaScript OCR library that extracts text from images in over 100 languages. It runs in browsers via WebAssembly and on Node.js, wrapping the Tesseract engine without modifying its recognition model.

A modern C++ toolkit providing machine learning algorithms and tools for data analysis and real-world application development.

EasyOCR is a ready-to-use optical character recognition library supporting 80+ languages and major writing scripts. It offers a simple Python API and CLI, with PyTorch-based detection and recognition models, plus options for custom training.

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.

Label Studio is an open-source, multi-type data labeling tool supporting audio, text, images, video, and time series with a simple UI and export to various model formats.

X-AnyLabeling is a cross-platform desktop application for AI-assisted annotation of image, video, text, and multimodal data, with many built-in deep learning models, diverse labeling tools, and multi-format import/export.

A comprehensive guide for AI/ML technical interviews at big tech companies, covering coding, ML fundamentals, system design, and behavioral prep, with an optional MCP-based AI tutor.

This open-source collection features AI Agent books, tutorials, and code repositories from GitHub, covering LLM Agent resources, courses, and frameworks. It supports daily automatic Star count updates, sorting by popularity, and provides recommended reading paths for developers and learners.

ModelScope is an open-source Python library implementing Model-as-a-Service, offering unified pipeline, Trainer and MsDataset interfaces for inference, fine-tuning and evaluation of CV, NLP, audio, multi-modal and scientific models, plus model/dataset hub integration.

einops is a flexible tensor operations library using Einstein-like notation for readable, reliable code across PyTorch, JAX, TensorFlow, NumPy and more.

Hugging Face Transformers is a model-definition framework for machine learning across text, vision, audio, and multimodal tasks. It provides a unified API for inference and training with over 1 million pretrained checkpoints.