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Introduction to Linear Algebra

di Gilbert Strang

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361371,134 (4.17)1
Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains the quality of earlier editions while at the same time seeing numerous minor improvements and major additions. The latter include: a new chapter on singular values and singular vectors, including ways to analyze a matrix of data; a revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages; a new section on linear algebra and cryptography; and a new chapter on linear algebra in probability and statistics. A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (e.g. practice problems, exams, development of textbook examples), plus codes in MATLAB, Julia, and Python.… (altro)
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评价最好的一本线性代数,没有之一。并且有麻省理工大学教授同步讲课,国内清华大学马辉教授也有按照这本书讲课。
比我见过的其他教材都要形象明了  次书是 MIT 线性代数课程的教材,同时Strang 教授的讲课录像也可以在MIT的开放课程网站下载。 每一章都是从一个小小的例子出发,然后到稍微复杂一点例子。这些例子非常简单,有的仅仅只是涉及到2x2矩阵的问题,大量的图片以及结合matlab的例子,给人以非常直观的感受,似乎读者以及从例子触及到了其中的奥妙。然后再提出某一个或者定义或者定理或者推论。然后稍加证明。接着又是一些例子。不过此时的例子更加实际更加具有应用性。读完之后思路之清晰前所未有! ( )
  MarcWang | Jul 17, 2017 |
After reading Gilbert Strang's book on Linear Algebra, well, it all made sense.

I must say, first off, that Linear Algebra and I have a bit of a shady past. The course covering it in the most depth did not agree with me initially in college, so I was forced to try to defeat this foe once again. Since then, I have read the entirety of this book, as most mathematics courses only use a strict subset of the text in the teaching of the class.

So what's the big deal about Linear Algebra? Well, for starters, did you know that the concept of it came before any practical application was discovered? Crazy, huh? Nowadays, though, it has all sorts of applications. For example, you could use matrices and vectors to solve multiple unknowns in a system of equations. Or, you could use a 4 x n matrix to represent a 3-dimensional object, allowing you to change the viewing angle with a 4 row vector. Or even, you could use linear algebra to solve problems dealing with imaginary numbers (where the real line is x and the imaginary line is the perpendicular y).

Wow!

So, this book, written by a man who's as devoted to the subject as you can get, writes about linear algebra beautifully, and even lays it out in an aesthetic manner using LaTeX, letting a computer deal with the finer points of readable layout, the way it should be!

I highly recommend this book to anybody dealing with any mathematics higher than trigonometry, at least as a reference. It can be loads of help for computer scientists as well (especially graphics programmers).

Though I recommend having some background in Algebra, Trigonometry, and Pre-Calculus before attempting all the chapters of this book. ( )
2 vota aethercowboy | Jul 8, 2009 |
I used it in my class. ( )
  m.vavalis | Jul 30, 2009 |
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May I dedicate this book to grandchildren who are very precious: Roger, Sophie, Kathryn, Alexander, Scott, Jack, William, Caroline, and Elizabeth. I hope you might take linear algebra one day. Especially I hope you like it. The author is proud of you.
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The heart of linear algebra is in two operations—both with vectors.
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Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains the quality of earlier editions while at the same time seeing numerous minor improvements and major additions. The latter include: a new chapter on singular values and singular vectors, including ways to analyze a matrix of data; a revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages; a new section on linear algebra and cryptography; and a new chapter on linear algebra in probability and statistics. A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (e.g. practice problems, exams, development of textbook examples), plus codes in MATLAB, Julia, and Python.

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