by David Cherney, Tom Denton, Andrew Waldron
Publisher: UC Davis 2013
Number of pages: 410
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. Our goal in writing it was to produce students who can perform computations with linear systems and also understand the concepts behind these computations.
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by Peter Saveliev - Intelligent Perception
This is a textbook for a one-semester course in linear algebra and vector spaces. An emphasis is made on the coordinate free analysis. The course mimics in some ways a modern algebra course. Calculus is a prerequisite for the course.
by Stephen Boyd, Lieven Vandenberghe - Cambridge University Press
This groundbreaking textbook covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, data science, machine learning, signal processing, tomography, navigation, control, etc.
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.
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.