Published by Minireference Co. 2020-10, 2020
ISBN 10: 0992001021 ISBN 13: 9780992001025
Language: English
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Paperback. Condition: new. 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Minireference Co. 10/25/2020, 2020
ISBN 10: 0992001021 ISBN 13: 9780992001025
Language: English
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Add to basketPaperback. Condition: new. 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketCondition: New. Über den AutorrnrnIvan 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. Tutoring made him realize that understanding connec.
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Add to basketPaperback. Condition: new. 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.
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
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