Table of Contents

1. Fundamental Math Courses
2. Neuroscience, Cognitive Science, etc.
3. Machine Learning/AI
4. More Math Courses
5. Datasets
6. Doing Research
7. Writing Papers
8. Personal List of Resources by Topic
9. Problem Solving (e.g. Debugging)
10. Codebases

You might also be interested in my PhD Resources page.

If you'd like to add to this, please submit a pull request on Github or send me an email with content at wcarvalho92@gmail.com.

-- Wilka Carvalho

---

General Self-Study

• Metacademy - organized resources and roadmaps for self-studying various topics led by Professor Roger Grosse @ The University of Toronto
  • Course Guides
  • Roadmaps (e.g. Differential geometry for machine learning, programming, etc.)

Other people's resource pages

• Qihong Lu - neuroscience PhD student @ Princeton