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Awesome List
A curated list of awesome Machine Learning frameworks, libraries and software.
GitHub stars and default-branch commits for josephmisiti/awesome-machine-learning.
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🤗 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!
A toolkit for developing and comparing reinforcement learning algorithms.
💫 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.
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.
Minimalist ML framework for Rust
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Interactive Data Visualization in the browser, from Python
A computer algebra system written in pure Python
A hyperparameter optimization framework
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
A standard API 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
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.
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 🚀
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.
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.
Fit interpretable models. Explain blackbox machine learning.
Image processing in Python
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
A scikit-learn compatible neural network library that wraps PyTorch
Rust bindings for the C++ api of PyTorch.
An Engine-Agnostic Deep Learning Framework in Java
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Fast data visualization and GUI tools for scientific / engineering applications
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Main repository for Vispy
Algorithmic Trading in Python with Machine Learning
Accelerated deep learning R&D
Python Toolkit for Causal and Probabilistic Reasoning
🔅 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