Introduction to Applied Linear Algebra: Vectors, Matrices and Least Squares
by Stephen Boyd, Lieven Vandenberghe
Publisher: Cambridge University Press 2018
Number of pages: 473
This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance.
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by Sergei Treil
This book covers a first course of linear algebra, it introduces mathematically advanced students to rigorous proof and formal definitions. The author of the text tried to emphasize topics important for analysis, geometry and probability.
by W. Keith Nicholson - Lyryx
The aim of the text is to achieve a balance among computational skills, theory, and applications of linear algebra. It is a relatively advanced introduction to the ideas and techniques of linear algebra targeted for science and engineering students.
by David Cherney, Tom Denton, Andrew Waldron - UC Davis
This textbook is suitable for a sophomore level linear algebra course taught in about twenty-five lectures. It is designed both for engineering and science majors, but has enough abstraction to be useful for potential math majors.
by Kenneth Kuttler - The Saylor Foundation
Introduction to linear algebra where everything is done with the row reduced echelon form and specific algorithms. The notions of vector spaces and linear transformations are at the end. Intended for a first course in linear algebra.