Linear Algebra Linear Algebra with Applications by Bretscher

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"Linear Algebra with Applications" by Otto Bretscher is praised for its clear writing style, effective examples, and engaging historical context, making it a valuable resource for linear algebra courses. The book covers essential topics such as linear equations, transformations, subspaces, orthogonality, determinants, eigenvalues, and linear differential equations. While some readers criticize the notation as unconventional, others appreciate its inventive visual approach. Overall, the text is well-received for its clarity and humor, enhancing the learning experience for students.

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Table of Contents:
Code:
[LIST]
[*] Text Features
[*] Preface
[*] Linear Equations
[LIST]
[*] Introduction to Linear Systems
[*] Matrices, Vectors, and Gauss-Jordan Elimination
[*] On the Solutions of Linear Systems; Matrix Algebra
[/LIST]
[*] Linear Transformations
[LIST]
[*] Introduction to Linear Transformations and Their Inverses
[*] Linear Transformations in Geometry
[*] Matrix Products
[*] The Inverse of a Linear Transformation
[/LIST]
[*] Subspaces of Mn and Their Dimensions
[LIST]
[*] Image and Kernel of a Linear Transformation
[*] Subspaces of R^n; Bases and Linear Independence
[*] The Dimension of a Subspace of R^n
[*] Coordinates
[/LIST]
[*] Linear Spaces
[LIST]
[*] Introduction to Linear Spaces
[*] Linear Transformations and Isomorphisms
[*] The Matrix of a Linear Transformation
[/LIST]
[*] Orthogonality and Least Squares
[LIST]
[*] Orthogonal Projections and Orthonormal Bases
[*] Gram-Schmidt Process and QR Factorization
[*] Orthogonal Transformations and Orthogonal Matrices
[*] Least Squares and Data Fitting
[*] Inner Product Spaces
[/LIST]
[*] Determinants
[LIST]
[*] Introduction to Determinants
[*] Properties of the Determinant
[*] Geometrical Interpretations of the Determinant; Cramer’s Rule
[/LIST]
[*] Eigenvalues and Eigenvectors
[LIST]
[*] Dynamical Systems and Eigenvectors: An Introductory Example
[*] Finding the Eigenvalues of a Matrix
[*] Finding the Eigenvectors of a Matrix
[*] Diagonalization
[*] Complex Eigenvalues
[*] Stability
[/LIST]
[*] Symmetric Matrices and Quadratic Forms
[LIST]
[*] Symmetric Matrices
[*] Quadratic Forms
[*] Singular Values
[/LIST]
[*] Linear Differential Equations
[LIST]
[*] An Introduction to Continuous Dynamical Systems
[*] The Complex Case: Euler’s Formula
[*] Linear Differential Operators and Linear Differential Equations
[/LIST]
[*] Appendix: Vectors
[*] Answers to Odd-Numbered Exercises
[*] Subject Index 
[*] Name Index
[/LIST]
 
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Using this book in my linear algebra course right now and I love the writing style, very clear examples and approach. There's even very cool historical examples, and splashes of wit/humor, but tastefully done.

It's been criticized by some for some of it's notation, which people seem not to like or find weird, but which I actually find cool, but I'm a fan of inventive visual notation.

-Dave K
 
Many years ago, as the internet was coming of age, I burned over 500 pounds of technical manuals. I realized I can look things up on the internet faster than I can find something in a technical manual. And just about anything I might need could be found online. But letting go of my several shelves worth of college text and other science books is another matter. I can't bring myself to get rid of them but there is very little if anything I can't find online now. Books are heavy and a pain...

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