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 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 Andrew Baker - University of Glasgow
The text covers basic ideas and techniques of Linear Algebra that are applicable in many subjects including the physical and chemical sciences, and statistics. These notes were originally written for a course at the University of Glasgow.
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 Ruslan Sharipov - Samizdat Press
This is a textbook of multidimensional geometry and linear algebra for the first year students. It covers linear vector spaces and linear mappings, linear operators, dual space, bilinear and quadratic forms, Euclidean spaces, Affine spaces.