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 Katta G. Murty
A sophomore level book on linear algebra and n-dimensional geometry with the aim of developing in college entering undergraduates skills in algorithms, computational methods, and mathematical modeling. Written in a simple style with lots of examples.
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 W. Keith Nicholson - Lyryx
The aim of the text is to achieve a balance among computational skills, theory, and applications of linear algebra. It is a relatively advanced introduction to the ideas and techniques of linear algebra targeted for science and engineering students.
by Kenneth Kuttler - The Saylor Foundation
Introduction to linear algebra where everything is done with the row reduced echelon form and specific algorithms. The notions of vector spaces and linear transformations are at the end. Intended for a first course in linear algebra.