9780992001025-0992001021-No bullshit guide to linear algebra

No bullshit guide to linear algebra

ISBN-13: 9780992001025
ISBN-10: 0992001021
Edition: 2nd V2.2 ed.
Author: Ivan Savov
Publication date: 2017
Publisher: Minireference Co.
Format: Paperback 596 pages
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Book details

ISBN-13: 9780992001025
ISBN-10: 0992001021
Edition: 2nd V2.2 ed.
Author: Ivan Savov
Publication date: 2017
Publisher: Minireference Co.
Format: Paperback 596 pages

Summary

No bullshit guide to linear algebra (ISBN-13: 9780992001025 and ISBN-10: 0992001021), written by authors Ivan Savov, was published by Minireference Co. in 2017. With an overall rating of 3.5 stars, it's a notable title among other Geometry & Topology (Mathematics) books. You can easily purchase or rent No bullshit guide to linear algebra (Paperback) from BooksRun, along with many other new and used Geometry & Topology books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $13.99.

Description

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.

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