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 Arak Mathai, Hans J. Haubold - De Gruyter Open
This textbook on linear algebra is written to be easy to digest by non-mathematicians. It introduces the concepts of vector spaces and mappings between them without dwelling on theorems and proofs too much. It is also designed to be self-contained.
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 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 Jim Hefferon - Saint Michael's College
This is an undergraduate linear algebra textbook, it covers linear systems, Gauss' method, vector spaces, linear maps and matrices, determinants, and eigenvectors and eigenvalues. Each chapter is followed by additional topics and applications.