Name: Matrix Analysis and Applied Linear Algebra
ISBN: 9780898714548

Matrix Analysis and Applied Linear Algebra

This book avoids the traditional definition-theorem-proof format; instead a fresh approach introduces a variety of problems and examples all in a clear and informal style. The in-depth focus on applications separates this book from others, and helps students to see how linear algebra can be applied to real-life situations. Some of the more contemporary topics of applied linear algebra are included here which are not normally found in undergraduate textbooks. Theoretical developments are always accompanied with detailed examples, and each section ends with a number of exercises from which students can gain further insight. Moreover, the inclusion of historical information provides personal insights into the mathematicians who developed this subject. The textbook contains numerous examples and exercises, historical notes, and comments on numerical performance and the possible pitfalls of algorithms. Solutions to all of the exercises are provided, as well as a CD-ROM containing a searchable copy of the textbook.

What Hacker News says

geokonAug 2026

I really recommend Matrix Analysis and Applied Linear Algebra by Carl Meyer. It's both concise and comprehensive. Strange is very good, but feels kinda vague and long winded in comparison (very good for a high level understanding of the tools you're dealing with)

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zhamisenJun 2022

I think you'll enjoy Matrix Analysis and Applied Linear Algebra from Carl Meyer: http://matrixanalysis.com/

Almost every topic is illustrated with an application or illustrative example, and the applications are very interesting.

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vitorsrJan 2022

In my honest view this is a bad example. Axler is a professor of mathematics and editor of multiple undergraduate and graduate mathematics texts series. His supervisor’s supervisor was Paul Halmos.

His books are introductory in the context of mathematics courses. They are not introductory in applied mathematical sciences contexts.

There I would suggest, e.g., Boyd and Vandenberghe’s Introduction to Applied Linear Algebra [1], Meyer’s Matrix Analysis and Applied Linear Algebra [2], Golub and Van Loan’s Matrix Computations [3] etc.

> But the book doesn’t like determinants and isn’t focused on computing things around matrices [...].

This is purposeful.

[1] https://web.stanford.edu/~boyd/vmls

[2] http://matrixanalysis.com

[3] https://www.cs.cornell.edu/cv/cvl_home/books

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vector_spacesNov 2020

My sense is that Vandenberghe is great for getting your feet wet and building intuition, but it's not as deep as Strang in its coverage and has fewer problems. Definitely still worth reading through especially since the problems lend themselves well to working through with Julia or Python or similar.

For further reading, try Matrix Analysis and Applied Linear Algebra by Meyer.

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geokonFeb 2019

have you looked at "Matrix Analysis and Applied Linear Algebra" by Carl Meyer? it seems very in line with what you're saying and the exercises are absolutely excellent. I've slowly made my way half way through the book and am very happy over all

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geokonNov 2018

Where is the text? Or is this an advertisement for a book?

Since this might get the right eyeballs here:

1. Does anyone have a good intuitive explanation for the meaning of the transpose operation? It seems to tie into a central symmetry between columns and rows (or equations and variables) that I'm having trouble articulating for myself

2. Why does every linear algebra book have a chapter on norms? It's always so incredibly boring and esoteric and I still haven't hit a situation where it's strictly necessary. The 2-norm seem adequate for most situations and comes out naturally from the least squares problem

PS: Strang is great. Meyer's "Matrix analysis and applied linear algebra" is even better (but more advanced)

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