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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The book was designed specifically for students who had not previously been exposed to mathematics as mathematicians view it. That is, as a subject whose goal is to rigorously prove theorems starting from clear consistent definitions.
by Edwin H. Connell
Covers abstract algebra in general, with the focus on linear algebra, intended for students in mathematics, physical sciences, and computer science. The presentation is compact, but still somewhat informal. The proofs of many theorems are omitted.
by Robert A. Beezer - University of Puget Sound
Introductory textbook for college-level sophomores and juniors. It covers systems of linear equations, matrix algebra, finite-dimensional vector spaces, matrix representations of linear transformations, diagonalization, Jordan canonical form, etc.
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.