Awesome Machine Learning

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Deep Learning for humans

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

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

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

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/

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.

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

A computer algebra system written in pure Python

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.

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

Lime: Explaining the predictions of any machine learning classifier

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

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.

Production infrastructure for machine learning at scale

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Image processing in Python

A Python wrapper for Google Tesseract

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

A scikit-learn compatible neural network library that wraps PyTorch

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Fast data visualization and GUI tools for scientific / engineering applications

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Main repository for Vispy

Algorithmic Trading in Python with Machine Learning

Python Toolkit for Causal and Probabilistic Reasoning

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai

An intuitive library to add plotting functionality to scikit-learn objects.

Build, run and scale AI agents like API and microservices - observable,auditable and identity-aware from day one.

Feature engineering and selection open-source Python library compatible with sklearn.

Machine learning with dataframes

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

A security scanner for your LLM agentic workflows

ML powered analytics engine for outlier detection and root cause analysis.

Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.

Serverless proxy for Spark cluster

A distributed Spark/Scala implementation of the isolation forest and extended isolation forest algorithms for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.