by Jonathan Gleason
Publisher: University of California 2018
Number of pages: 681
From the table of contents: K-modules and linear transformations; Linear independence, spanning, bases, and dimension; Coordinates, column vectors, and matrices; Eigenstuff; Multilinear algebra and tensors; Inner-product spaces; Applications.
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by Zico Kolter - Stanford University
From the tabble of contents: Basic Concepts and Notation; Matrix Multiplication; Operations and Properties; Matrix Calculus (Gradients and Hessians of Quadratic and Linear Functions, Least Squares, Eigenvalues as Optimization, etc.).
by George Benthien
Tutorial describing many of the standard numerical methods used in Linear Algebra. Topics include Gaussian Elimination, LU and QR Factorizations, The Singular Value Decomposition, Eigenvalues and Eigenvectors via the QR Method, etc.
by Simon J.A. Malham - Heriot-Watt University
From the table of contents: Linear second order ODEs; Homogeneous linear ODEs; Non-homogeneous linear ODEs; Laplace transforms; Linear algebraic equations; Matrix Equations; Linear algebraic eigenvalue problems; Systems of differential equations.
by Charles L. Byrne - University of Massachusetts Lowell
This book is a text for a graduate course that focuses on applications of linear algebra and on the algorithms used to solve the problems that arise in those applications. Tthe particular nature of the applications will prompt us to seek algorithms.