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 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.
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 Richard Barrett et al. - Society for Industrial Mathematics
The book focuses on the use of iterative methods for solving large sparse systems of linear equations. General and reusable templates are introduced to meet the needs of both the traditional user and the high-performance specialist.
by Leif Mejlbro - BookBoon
The book is a collection of solved problems in linear algebra. The second volume covers geometrical vectors, vector spaces and linear maps. All examples are solved, and the solutions usually consist of step-by-step instructions.