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 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 Peter Saveliev
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 Benjamin McKay - University College Cork
These notes are drawn from lectures given for a first year introduction to linear algebra. The prerequisites for this course are arithmetic and elementary algebra, and some comfort and facility with proofs, particularly using mathematical induction.