Getting Started with Machine Learning

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A community-driven place to get started with machine learning and AI. This list is not definite, nor sequential, but we hope it’s a good starting place for anyone looking to get into the field. All resources mentioned in this guide are free, and include a little description of why they are useful. Each section has a set of starting points (usually courses, books, blog posts, etc.), relevant papers and project ideas. The most helpful starting points in each section are marked with a ⭐️.

Remember: The two best things you can do are building stuff and running your own experiments.

Contents

  1. Basics
  2. Mathematics
  3. Neural Networks
  4. Computer Vision
  5. Natural Language Processing (NLP)
  6. Reinforcement Learning (RL)
  7. Generative Adversarial Networks (GANs)
  8. Ethics
  9. Community
  10. Contributing

Basics

Resources

Mathematics

Calculus

Linear Algebra

Statistics

Neural Networks

Papers
Project ideas

Computer Vision

Papers
Project ideas

Natural Language Processing

Papers

Coming soon - Open a PR!

Project ideas

Coming soon - Open a PR!

Reinforcement Learning

Papers

Coming soon - Open a PR!

Project ideas

Generative adversarial networks

Papers

Ethics

Papers
Project ideas

Community

You can’t learn hard things alone. Fortunately, there’s a great community ready to help out.

Resources

Blogs / publications

Newsletters

Discussion

Papers

Contributing to gettingstarted.ml

Thanks for even considering contributing! This guide is community driven, and every pull request is appreciated. Whether you are fixing a typo, adding or updating resources - everything will help make this guide better for everyone. Please be careful when submitting your own content, this is not a place for self promotion but we do value good learning materials. On behalf of every beginner, thank you!


Edit on GitHub · Created by Rick Wierenga