Free PDF Coding the Matrix: Linear Algebra through Applications to Computer Science, by Philip N. Klein
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Coding the Matrix: Linear Algebra through Applications to Computer Science, by Philip N. Klein
Free PDF Coding the Matrix: Linear Algebra through Applications to Computer Science, by Philip N. Klein
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An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program. Mathematical concepts and computational problems are motivated by applications in computer science. The reader learns by doing, writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications. Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. A companion web site, codingthematrix.com provides data and support code. Most of the assignments can be auto-graded online. Over two hundred illustrations, including a selection of relevant xkcd comics.
Chapters: The Function, The Field, The Vector, The Vector Space, The Matrix, The Basis, Dimension, Gaussian Elimination, The Inner Product, Special Bases, The Singular Value Decomposition, The Eigenvector, The Linear Program
- Sales Rank: #70118 in Books
- Published on: 2013-09-03
- Original language: English
- Number of items: 1
- Dimensions: 11.00" h x 1.24" w x 8.50" l, 2.79 pounds
- Binding: Paperback
- 548 pages
About the Author
Philip Klein is Professor of Computer Science at Brown University. He was a recipient of the National Science Foundation’s Presidential Young Investigator Award, and has received multiple research grants from the National Science Foundation. He has been made an ACM Fellow in recognition of his contributions to research on graph algorithms. He is a recipient of Brown University’s Award for Excellence in Teaching in the Sciences. Klein received a B.A. in Applied Mathematics from Harvard and a Ph.D. in Computer Science from MIT. He has been a Visiting Scientist at Princeton’s Computer Science Department, at MIT’s Mathematics Department, and at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), where he is currently a Research Affiliate. Klein has worked at industry research labs, including Xerox PARC and AT&T Labs, and he has been Chief Scientist at three start-ups. Klein was born and raised in Berkeley, California. He started learning programming in 1974, and started attending meetings of the Homebrew Computer Club a couple of years later. His love for computer science has never abated, but in a chance encounter with E. W. Dijkstra in 1979, he was told that, if he wanted to do computer science, he had better learn some math. His favorite xkcd is 612.
Most helpful customer reviews
92 of 95 people found the following review helpful.
Many typos in first version
By Philly Filly
I found this book invaluable while taking the author's course Coding the Matrix on coursera.org. However, this first version was rushed to press with insufficient editing. It is rife with typos, some of which could mislead readers not already familiar with linear algebra. The index is both skimpy and inaccurate. Unless you currently need this book for a course, I recommend waiting for a corrected edition.
57 of 57 people found the following review helpful.
The Kindle version is not the same as recent printed versions and contains errors long since corrected in the print format.
By Ted Hoffman
This review is specific to the Kindle version of the book.
The textbook as intended is excellent. As many other readers have noted going back several years, the 1st edition of this book had an over abundance of typographical errors which have been corrected in more recent print versions. Amazon advertises the publication date for the Kindle version as April 7, 2015 but it contains all of the original typographical errors.
When I purchased the Kindle version I knew about the typographical errors of the first edition and I also knew that the recent print editions had been corrected. I purchased the Kindle version as it had a very recent publication date and I was reasonably expecting that it would have been based on a corrected version of the text. I was really disappointed that this was not the case.
While existing print copies of a book can't be updated, the same is not true for digital formats. Amazon has cheapened the Kindle brand by selling old versions of books and tagging them with recent publication dates.
Amazon should be correcting the Kindle version and providing updated versions to all of the readers who have purchased faulty copies.
43 of 46 people found the following review helpful.
An interesting approach to linear algebra
By Arko
The book presents a fresh look at linear algebra. You'd learn things by coding in Python. The way vectors and matrices are treated are quite interesting and different from how they are treated in standard linear algebra libraries. The book guides you to develop a whole linear algebra library from scratch and learn things along the way.
You need to be reasonably comfortable coding in Python to fully appreciate the approach presented in this book. The book has a hands on approach and you need to do the coding exercises to fully appreciate the material presented. If you're not comfortable with Python or don't really want to do coding this book may not be for you. However, if you like programming in Python this is an excellent book to learn/review linear algebra.
The reason I'm giving it 4 stars is because the book contains a huge amount of typos. If you're somewhat comfortable with the subject you'd be able to figure them out but they are a constant annoyance nonetheless.
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