Schaum's Outline of Theory and Problems of Matrix Operations

The text book was in excellent condition and arrived in a timely fashion. I recommend this book seller.

The author has a real knack at making the subject accessible and easy to assimilate. I would recommend you get this book before you go on to a more advanced book like Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)(3rd Edition). You can read this bit by bit, there are plenty of examples to drive the point home and it's easy to find what you are looking for. All this for a very low price. What more could you ask? Well, sure there could be more advanced topics, Householder matrices are only touched upon, but you'll pick that up easily when you are done with this book.

Unlike the Schaum's outline of linear algebra, which is more about the physical interpretation of matrices as vectors, this Schaum's outline is good for learning techniques of solutions that were meant for large matrices. It is aimed at the applied mathematician, since there are not very many proofs as exercises. Instead, the user is taught the various algorithms used to solve matrix problems. The guide starts with very basic operations such as matrix addition, subtraction, and dot products. It then moves on to methods of solution for finding the determinant, eigenvalues and eigenvectors, and the functions of a matrix. What I particularly like about this guide is that in its more advanced section it shows in plain language how to implement singular value decomposition, the QR algorithm to compute eigenvalues, vector norms, LU decomposition, and other more advanced methods of solution that are not mentioned in basic linear algebra texts and are overloaded with theory in more advanced texts that lack practical examples. This book is an excellent companion to texts such as Trefethen and Bau's "Numerical Linear Algebra", since that book is short on worked examples and concentrates more on theory. The format of this guide is the same of most other Schaum's outlines- for each topic there are a few pages on motivation and the algorithms themselves, a section of worked problems, and a section of more problems with answers but not with complete solutions.

Takes you right from the basics to complex stuff like QR decomposition and SVD. Very useful for programmers who want to gain knowledge on solving linear equations.

This is a very nice book that covers a everything one needs to know about matrices, without the extra derivations and confusion associated with this math. Very nice examples are included in the book that show the use of matrices.