No Bullshit Guide to Linear Algebra

By Ivan Savov

Book Overview

Linear algebra is the foundation of science and engineering. Knowledge of linear algebra is a prerequisite for studying statistics, machine learning, computer graphics, signal processing, chemistry, economics, quantum mechanics, and countless other applications. Indeed, linear algebra offers a powerful toolbox for modelling the real world.

The No Bullshit Guide to Linear Algebra shows the connections between the computational techniques of linear algebra, their geometric interpretations, and the theoretical foundations. This university-level textbook contains lessons on linear algebra written in a style that is precise and concise. Each concept is illustrated through definitions, formulas, diagrams, explanations, and examples of real-world applications. Readers build their math superpowers by solving practice problems and learning to use the computer algebra system SymPy to speed up tedious matrix arithmetic tasks.

"The book explains the concepts in a way that gives a strong intuitive understanding." - Joe Nestor, student

"It's very well written and a fun read " - Felix Kwok, professor

"I used this book in multiple big data courses when I needed a deeper understanding of the material." - Zane Zakraisek, student

The author, Ivan Savov, combines 17 years of tutoring experience with a B.Eng. in electrical engineering, an M.Sc. in physics, and a Ph.D. in computer science from McGill University.

• Format: Paperback
• Language: English
• ISBN: 0992001021
• ISBN13: 9780992001025
• Release Date: April 2017
• Publisher: Minireference Co.
• Length: 596 Pages
• Weight: 1.62 lbs.
• Dimensions: 1.2" x 5.5" x 8.5"

Customer Reviews

Very clear and succinct

This book goes into enough detail in introducing linear algebra. So far I have gone through half the book (up to chapter 7), and I had no linear algebra knowledge prior to reading this. It was all enough to introduce the main concepts for my graduate studies in data science