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

Deep Learning for humans

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

Streamlit — 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. 🌟 Star to support our work!

Caffe: a fast open framework for deep learning.

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

💫 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

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

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

A hyperparameter optimization framework

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

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.

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.

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

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.

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

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

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.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Fit interpretable models. Explain blackbox machine learning.

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

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

A scikit-learn compatible neural network library that wraps PyTorch

⚡ Pure-Rust WebGPU inference engine — OpenAI-API compatible, GGUF native, runs on any GPU. No Python. No llama.cpp. Single binary.

Rust bindings for the C++ api of PyTorch.

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

An Engine-Agnostic Deep Learning Framework in Java

A Rust machine learning framework.

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

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.

AI Infra / AI Orchestration / AI Control Plane

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Fast, flexible and easy to use probabilistic modelling in Python.

Algorithmic Trading in Python with Machine Learning

Accelerated deep learning R&D

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

a delightful machine learning tool that allows you to train, test, and use models without writing code

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.