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 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 W W L Chen - Macquarie University
Linear equations, matrices, determinants, vectors, vector spaces, eigenvalues and eigenvectors, linear transformations, real inner product spaces, orthogonal matrices, applications of real inner product spaces, complex vector spaces.
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.
The book was designed specifically for students who had not previously been exposed to mathematics as mathematicians view it. That is, as a subject whose goal is to rigorously prove theorems starting from clear consistent definitions.