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.
Home page url
Download or read it online for free here:
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 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.
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 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.