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Coding the Matrix: Linear Algebra through Applications to Computer Science Paperback – 3 Sep 2013

4.4 out of 5 stars 8 customer reviews

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Product details

  • Paperback: 548 pages
  • Publisher: Newtonian Press; 1 edition (3 Sept. 2013)
  • Language: English
  • ISBN-10: 0615880991
  • ISBN-13: 978-0615880990
  • Product Dimensions: 21.6 x 3.1 x 27.9 cm
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (8 customer reviews)
  • Amazon Bestsellers Rank: 266,802 in Books (See Top 100 in Books)

Product Description

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.


Customer Reviews

4.4 out of 5 stars
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Top Customer Reviews

Format: Paperback Verified Purchase
After watching the coursera course and using the discussion forums for questions I find this book useful to have. Without having any knowledge of Python or some knowledge of Linear Algebra I think it is very difficult to follow this course. I believe it will be very difficult to self-study linear algebra through this book without following the coursera course (and the discussion forums).

It is very nice that this books combines real computer science applications and demonstrate how linear algebra is used to solve them. This is the most nice part of this book.
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Format: Kindle Edition Verified Purchase
This book is great and the teacher is great - but I have a problem I cannot read the kindle version in Kindle Cloud Reader, this is a huge disappointment as I need to be able to read the book on various devices including my PC at work.
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Format: Paperback Verified Purchase
Coding the Matrix is the (none essential) text book to accompany the author's course of the same name at Brown University, and now available on Coursera. This introduces Linear Algebra to an audience with programming experience. In addition to Python code examples, the book also distinguishes itself through the use of example scenarios that are meaningful to computing students.
The material in the book is straightforwardly expressed and accessible. It slightly extends the Coursera lectures, and supporting slides, but a reader unfamiliar with these would not recognise that origin.

There are exercises in each chapter, which are from the online course. There are however no solutions. It is though substantially easier to follow the examples in printed form. For me, the book has one further advantage over the on-line material - It has an index! This is invaluable when you are trying to find something again that was only half understood from the lectures.
At 510 pages and US legal (almost A4) size, this is a substantial book and a useful addition to the course material. Full credit to Amazon for charging the same in the UK as the US.
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Format: Paperback Verified Purchase
Interesting and fun approach. However, the writing is often unclear and bars understanding - which is a shame. I am not following the coursera course, which may facilitate this understanding. The book is by no means unreadable, but is more work than it should be.
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