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 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 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 Paul Dawkins - Lamar University
These topics are covered: Systems of Equations and Matrices; Determinants; Euclidean n-space; Vector Spaces; Eigenvalues and Eigenvectors. These notes do assume that the reader has a good working knowledge of basic Algebra.
by J. Strom, K. Astrom, T. Akenine-Moller - immersivemath
This is a linear algebra book built around interactive illustrations. Each chapter starts with an intuitive concrete example that practically shows how the math works using interactive illustrations. After that, the more formal math is introduced.