π€ Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A curated list of awesome Machine Learning frameworks, libraries and software.
Open Data Platform for analysts, quants and AI agents.
Learn AI Engineering! Learn it. Build it. Ship it for others.
scikit-learn: machine learning in Python
Deep Learning for humans
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 β object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
We write your reusable computer vision tools. π
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.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
A community-supported supercharged document management system: scan, index and archive all your documents
Streamlit β A faster way to build and share data apps.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Build and share delightful machine learning apps, all in Python. π Star to support our work!
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
π« Industrial-strength Natural Language Processing (NLP) in Python
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols IβIV) β’ Harvard CS249r | https://mlsysbook.ai
The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.
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.
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
A reactive notebook for Python β run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Universal LLM Deployment Engine with ML Compilation
100-Days-Of-ML-CodeδΈζη
π€ The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Best Practices on Recommendation Systems
Open standard for machine learning interoperability
Machine Learning Engineering Open Book
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Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Datasets, Transforms and Models specific to Computer Vision
ARIS βοΈ (Auto-Research-In-Sleep) β Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in β works with Claude Code, Codex, OpenClaw, or any LLM agent.
High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.
π¦ Data Versioning and ML Experiments
A hyperparameter optimization framework
NLTK Source
A very simple framework for state-of-the-art Natural Language Processing (NLP)
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Open Machine Learning Compiler Framework
Build voice agents with open-source models
Low-code framework for building custom LLMs, neural networks, and other AI models
π Geometric Computer Vision Library for Spatial AI
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Minimal and clean examples of machine learning algorithms implementations
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Fast and Accurate ML in 3 Lines of Code
X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, point cloud and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
Build, Manage and Deploy AI/ML Systems
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A unified framework for machine learning with time series
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
TensorFlow-based neural network library
RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]
Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop β all through one unified, production-ready inference API.
A python library for user-friendly forecasting and anomaly detection on time series.
Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.