Books & learningPublished

Visualize it. Derive it. Build it yourself.

Machine Learning Refined is a textbook coauthored by Jeremy Watt, Reza Borhani, and Aggelos Katsaggelos. The second edition pairs geometric intuition and mathematical foundations with hands-on Python implementations, supported by freely available chapter PDFs, notebooks, exercises, and lecture slides.

Explore the bookFor independent learners, students, and instructors exploring machine learning

Machine Learning Refined

Second edition

Foundations, Algorithms, and Applications.

By Jeremy Watt, Reza Borhani, and Aggelos Katsaggelos. Published by Cambridge University Press.

TextbookPython notebooksOpen resources

The job

Make the hard part explicit.

Machine learning can feel like a collection of opaque APIs. Learning the ideas beneath them requires a connection between visual intuition, mathematical reasoning, and code you can work through yourself.

The approach

Build around the real workflow.

Each topic moves from a visual explanation to a mathematical derivation and a practical implementation. Companion notebooks, exercises, and teaching materials make that process accessible to independent learners and classrooms alike.

The distinction

Keep the product focused.

Coauthored by Jeremy Watt, Reza Borhani, and Aggelos Katsaggelos and published by Cambridge University Press, the book teaches the fundamentals by building them from scratch. Its open companion resources let readers explore the material directly.

How it helps