Awesome Machine Learning

An Open Source Machine Learning Framework for Everyone

🤗 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

Open Source Computer Vision Library

Deep Learning for humans

Ultralytics YOLO 🚀

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

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

Apache Spark - A unified analytics engine for large-scale data processing

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

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

Making large AI models cheaper, faster and more accessible

A toolkit for developing and comparing reinforcement learning algorithms.

结巴中文分词

Caffe: a fast open framework for deep learning.

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

💫 Industrial-strength Natural Language Processing (NLP) in Python

Visualizer for neural network, deep learning and machine learning models

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

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

The fastai deep learning library

MLX: An array framework for Apple silicon

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.

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

Data Apps & Dashboards for Python. No JavaScript Required.

Graph Neural Network Library for PyTorch

Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative configs with command line and CI/CD integration. Used by OpenAI and Anthropic.

Interactive Data Visualization in the browser, from Python

Minimalist ML framework for Rust

Zipline, a Pythonic Algorithmic Trading Library

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

Apache Hadoop

Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

A computer algebra system written in pure Python

A hyperparameter optimization framework

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

Lime: Explaining the predictions of any machine learning classifier

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Statsmodels: statistical modeling and econometrics in Python

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

Bayesian Modeling and Probabilistic Programming in Python

Deep learning library featuring a higher-level API for TensorFlow.

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.