A hands-on approach to mastering linear algebra through Python code and mathematical intuition.
This book teaches linear algebra from the ground up, combining rigorous theory with practical Python implementations. Each concept is explained with clear intuition, mathematical formalism, and working code.
Paperback on Amazon | PDF version | Spanish PDF
Preview the book:
This repository contains all Python code from the book. Each chapter's concepts are implemented as standalone scripts and Jupyter notebooks that you can run, modify, and learn from.
Join the Discord server for questions and support: https://discord.gg/t9UAkKyR95
Expertly translated by Diana Llorente
Available on Amazon.es | Available as pdf
Preview:
The book's code has been independently translated by the community:
- R implementation: alexander-pastukhov.github.io/cohen-linear-algebra
- C++ implementation: github.com/thehoglet/LinAlgBook
- Core linear algebra concepts from vectors to eigendecomposition
- Geometric intuition behind mathematical operations
- Practical implementation in Python/NumPy
- Applications in machine learning and data science
| Format | Link |
|---|---|
| Paperback | Amazon |
| Gumroad | |
| SPANISH Paperback | |
| SPANISH PDF | Gumroad |
Mike X Cohen, PhD - Former neuroscience professor, full-time educator, and Udemy bestselling instructor with 25 years of experience teaching mathematics, machine learning, and data science.
All code in this repository is free to use for learning. The book provides the context, explanations, theory, proofs, and exercises.