Linear Algebra: Theory, Intuition, Code

A hands-on approach to mastering linear algebra through Python code and mathematical intuition.

About the Book

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:

• Table of Contents
• Free sample chapter: Matrix Multiplications

Code Repository

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.

Discord server

Join the Discord server for questions and support: https://discord.gg/t9UAkKyR95

Translations

Spanish Edition

Expertly translated by Diana Llorente

Available on Amazon.es | Available as pdf

Preview:

• Tabla de Contenidos
• Capítulo de muestra gratuito: Multiplicación de matrices

Community Translations

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

What You'll Learn

• 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

Purchase Options

| Format | Link | |--------|------| | Paperback | Amazon | | PDF | Gumroad | || SPANISH Paperback | Amazon.es | SPANISH PDF | Gumroad |

About the Author

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.

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All code in this repository is free to use for learning. The book provides the context, explanations, theory, proofs, and exercises.