#machine-learning

Open standard for machine learning interoperability

scikit-learn: machine learning in Python

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

A hyperparameter optimization framework

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Streamlit — A faster way to build and share data apps.

High-performance data engine for AI and multimodal workloads. Process images, audio, video, and structured data at any scale

🤗 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.

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Annotated data.

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

The Open Source Feature Store for AI/ML

The official CLI and Python client for the Hugging Face Hub.

🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning

🤗 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.

Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes

A reactive notebook for Python — 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.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Single-cell analysis in Python. Scales to >100M cells.

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

⚡ TabPFN: Foundation Model for Tabular Data ⚡

Open ABI and FFI for Machine Learning Systems

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Deep Learning for humans

Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.

:metal: TT-NN operator library, and TT-Metalium low level kernel programming model.

Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.