Foundations of Machine Learning

Vahid Seydi · a draft in progress · companion to the free lecture course Foundations of Machine Learning

This book is the written companion to the lecture course. Each chapter covers one block of the course and each section covers one lecture, so section 1.1 is Session 01. The lectures give each idea as a picture and in speech; the book gives the full argument, the references and the exercises. Chapters appear here as they are written.

Chapters

• 1. The Landscape — sessions 01–04, in preparation
• 2. The Supervised Recipe — sessions 05–12, in preparation
• 3. Estimation, Priors, and Recursion — sessions 13–14, in preparation
• 4. Beyond the Parametric Line — sessions 15–18, in preparation
• 5. Classification — sessions 19–25, in preparation
• 6. Nonlinearity and Neural Networks — sessions 26–27, in preparation
• 7. Learning Without Labels — sessions 28–31, in preparation
• 8. Structure and Scarce Labels — sessions 32–33, in preparation
• 9. Text Data — sessions 34–35, in preparation
• 10. Graph Data — sessions 36–37, in preparation
• 11. Sequential Data — sessions 38–41, in preparation
• 12. Deep Sequence Models — session 42, in preparation
• 13. Recommender Systems — sessions 43–45, in preparation
• 14. Image Data — sessions 46–49, in preparation
• 15. Generative Models — sessions 50–51, in preparation
• 16. Learning by Interaction — sessions 52–55, in preparation
• 17. Honesty — sessions 56–58, in preparation

How to cite

@misc{seydi2026mlfoundations,
  author    = {Seydi, Vahid},
  title     = {Foundations of Machine Learning},
  year      = {2026},
  note      = {Draft},
  publisher = {Bluevision AI},
  url       = {https://books.bluevision-ai.org/ml-foundations/}
}

Please cite the book rather than a video: the videos point here. This page always carries the reference that is current.

Licence

The book text is © 2026 Vahid Seydi, all rights reserved, and free to read here. The course slides, figures, narration and videos are CC BY-NC 4.0; the lab notebooks are MIT.