No Bullshit Guide to Linear Algebra (Paperback)

Ivan Savov

ISBN 10: 0992001021 / ISBN 13: 9780992001025

Published by Minireference Co., 2020

About this Item

Paperback. 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, studentThe 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9780992001025

Bibliographic Details

• Title: No Bullshit Guide to Linear Algebra (Paperback)
• Publisher: Minireference Co.
• Publication Date: 2020
• Language: English
• ISBN 10: 0992001021
• ISBN 13: 9780992001025
• Binding: Paperback
• Edition: 2nd Edition
• Condition: new

About this title

Synopsis

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 15 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.

About the Author

I have been teaching math and physics for more than 15 years as a private tutor. My tutoring experience taught me how to explain concepts that people find difficult to understand. I've had the chance to experiment with different approaches for explaining challenging material. Fundamentally, I've learned from teaching that understanding connections between concepts is much more important than memorizing facts. It's not about how many equations you know, but about knowing how to get from one equation to another.

I completed my undergraduate studies at McGill University in electrical engineering, then did a M.Sc. in physics, and recently completed a Ph.D. in computer science. In my career as a researcher, I've been fortunate to learn from very inspirational teachers, who had the ability to distill the essential ideas and explain things in simple language. I want to recreate the same learning experience for you through my writing. I founded the Minireference Publishing company to revolutionize the textbook industry. We make textbooks that don't suck.