awesome-ai
github.com/awesomelistsio/awesome-ai ↗A curated list of awesome frameworks, libraries, tools, and resources for Artificial Intelligence (AI). This list covers everything from foundational machine learning and deep learning to specialized areas like NLP, computer vision, and AI ethics.
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me reinforcement learning resources from awesome-ai"
Installation instructions →What's inside
Reinforcement Learning
- Acme
A library of reinforcement learning algorithms by DeepMind.
- Ray RLlib
A scalable library for reinforcement learning built on Ray.
- RLlib
A scalable reinforcement learning library that integrates with Ray.
- Stable-Baselines3
A set of reliable implementations of reinforcement learning algorithms in Python.
- TF-Agents
A library for reinforcement learning in TensorFlow.
Community
- AI Alignment Forum
A community focused on AI alignment and safety research.
- AI Ethics Slack Group
A Slack group for discussions on AI ethics.
- Kaggle
A platform for data science competitions and community.
- PyTorch Forums
A forum for discussing PyTorch-related topics.
- Reddit: r/MachineLearning
A subreddit for discussions on machine learning.
AI Ethics
- AI Fairness 360
A toolkit for detecting and mitigating bias in machine learning models.
- EthicsNet
A community-driven project focused on ethical AI.
- Explainable AI (XAI)
DARPA’s initiative for explainable AI research.
- FAT Forensics
A toolkit for Fairness, Accountability, and Transparency in AI.
- Papers on AI Ethics
A collection of influential research papers on AI ethics.
Natural Language Processing (NLP)
- AllenNLP
An open-source research library for NLP, built on top of PyTorch.
- NLTK
The Natural Language Toolkit, a comprehensive library for text processing and analysis.
- spaCy
An open-source NLP library for advanced natural language processing in Python.
- Stanford NLP
A suite of NLP tools developed by the Stanford NLP Group.
- TextBlob
A simple library for processing textual data.
Deep Learning
- Apache MXNet
A scalable deep learning framework with a flexible programming model.
- DeepSpeed
A deep learning optimization library that makes distributed training easy and efficient.
- Hugging Face Transformers
A library for state-of-the-art natural language processing models.
- JAX
A library for high-performance numerical computing and automatic differentiation, designed for deep learning.
- ONNX
An open format for AI models, allowing interoperability between different deep learning frameworks.
AI for Edge Computing
- AWS IoT Greengrass
A service for deploying machine learning models on edge devices using AWS.
- Edge Impulse
A platform for developing machine learning models on edge devices.
- ONNX Runtime
A cross-platform, high-performance scoring engine for ONNX models.
- OpenVINO
An Intel toolkit for optimizing deep learning models for edge devices.
- TensorFlow Lite
A framework for running machine learning models on edge devices.
Machine Learning
- CatBoost
A gradient boosting library that handles categorical features automatically.
- Dask-ML
A scalable machine learning library that integrates with Dask for parallel computing.
- LightGBM
A fast, distributed, high-performance gradient boosting framework.
- MLflow
An open-source platform for managing the end-to-end machine learning lifecycle.
- XGBoost
A scalable and efficient gradient boosting framework.
Learning Resources
- Coursera: Machine Learning
An introductory machine learning course by Andrew Ng.
- Deep Learning Specialization
A comprehensive deep learning course by Andrew Ng.
- Fast.ai Courses
Free courses on deep learning and AI.
- Google AI Hub
A platform for AI research and learning by Google.
- PyTorch Tutorials
Official tutorials for learning PyTorch.
Showing a sample of 50 resources. View the full list on GitHub →