Introduction to Linear Algebra (Gilbert Strang) – Bookino
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Description

Gilbert Strang’s textbooks have changed the entire approach to learning linear algebra — away from abstract vector spaces to specific examples of the four fundamental subspaces: the column space and nullspace of A and A’.

This new fifth edition has become more than a textbook for the basic linear algebra course. That is its first purpose and always will be. The new chapters about applications of the SVD, probability and statistics, and Principal Component Analysis in finance and genetics, make it also a textbook for a second course, plus a resource at work. Linear algebra has become central in modern applied mathematics. This book supports the value of understanding linear algebra.

Introduction to Linear Algebra, Fifth Edition includes challenge problems to complement the review problems that have been highly praised in previous editions. The basic course is followed by eight applications: differential equations in engineering, graphs and networks, statistics, Fourier methods and the FFT, linear programming, computer graphics, cryptography, Principal Component Analysis, and singular values.

Audience: Thousands of teachers in colleges and universities and now high schools are using this book, which truly explains this crucial subject. This text is for readers everywhere, with support from the websites and video lectures. Every chapter begins with a summary for efficient review.

Contents: Chap. 1: Introduction to Vectors; Chap. 2: Solving Linear Equations; Chap. 3: Vector Spaces and Subspaces; Chap. 4: Orthogonality; Chap. 5: Determinants; Chap. 6: Eigenvalues and Eigenvectors; Chap. 7: Singular Value Decomposition; Chap. 8: Linear Transformations; Chap. 9: Complex Vectors and Matrices; Chap. 10: Applications; Chap. 11: Numerical Linear Algebra; Chap. 12: Linear Algebra in Probability and Statistics; Matrix Factorizations; Index; Six Great Theorems.

31 reviews for Introduction to Linear Algebra (Gilbert Strang)

4.8
Based on 31 reviews
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  1. Very thorough and good textbook

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  2. Professor Strang is fantastic

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  3. For the most part, I think it’s a good book that goes through a lot of concepts, though, I must agree with some previous reviewers in that, a lot of the stuff doesn’t feel completely clear, like explained properly.

    EDIT: After starting to watch the lectures while reading, I think this is a great resource. Unfortunately I should have been aware of that before writing this review, he’s a great professor!

    (0) (0)
  4. Every subtlety fully confronted for the practical application of linear algebra.

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  5. Anyone considering this text should start by watching some of Dr. Strang’s 18.06 lectures from MIT OCW, because this book channels his personality and style perfectly. Is that good? Maybe. Like his lectures, the book is full of brilliant insights and connections that occasionally meander, hinting at or touching on terms and ideas that aren’t yet carefully defined. Still, I find the text’s exposition clear enough despite the occasional meandering. The problem sets I’m more ambivalent about. I like that many problems try to reach beyond standard calculations and proofs to get at the conceptual thinking behind the ideas. But in their attempts to do that, they’re not always clearly stated and sometimes have misleading language. The basic task of a problem is not always evident and you end up guessing at what’s intended.

    This text would be a terrific supplement for a course taught in a computational manner that lacks conceptual depth. And it would be great for an experienced instructor to teach from, provided that they take care with their homework assignments. For independent study or review, it’s still pretty solid considering the available video lectures and recitations along with the free, complete solutions available on the book’s website. Just expect that if you start working random problems from the book then you might hit some clunkers.

    Overall, I admire the text – and Dr. Strang generally – very much. There are brilliant ideas and terrific problems here. I’d just like to see the problem sets tightened up a bit more.

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