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Algorithms
Get Free Ebook Algorithms
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Product details
Paperback: 336 pages
Publisher: McGraw-Hill Education; 1 edition (September 13, 2006)
Language: English
ISBN-10: 9780073523408
ISBN-13: 978-0073523408
ASIN: 0073523402
Product Dimensions:
7.3 x 0.5 x 9.2 inches
Shipping Weight: 1 pounds (View shipping rates and policies)
Average Customer Review:
4.0 out of 5 stars
68 customer reviews
Amazon Best Sellers Rank:
#89,914 in Books (See Top 100 in Books)
I like this book FAR more than the CLRS book that most introductory algorithms classes use. It is shorter (because it has a lot less fluff), and is much clearer in it's descriptions and examples than CLRS.
The actual textbook is an excellent introduction to basic classes of algorithms. Most things were pretty clear, and the chapter on NP-completeness ties everything together nicely when it discusses reductions. It is written in such a way that it is actually tolerable to sit down an read, as opposed to just use as a reference. My class was actually provided a pdf draft of the book for free, but I thought that this was one of the rare times where the amount of time I used the book would actually warrant having a physical copy. It's paperback, which is nice for not adding any weight to my already unnecessarily full backpack, but it feels a bit cheaper than you would expect the printing of a $40+ black and white textbook to be.
Next to the popular algorithms books (CLRS, Sedgewick/Wayne, Skiena, Roughgarden) this book looks impossibly slim. However it is a concise and complete overview of algorithms, and maybe the most easily readable. It does not have all the mathematical proofs of CLRS, or as much source code as Sedgewick/Wayne. But it does give you enough to grasp the fundamentals and think about how to apply them in your daily work.My only criticism is that the index is ridiculously short.And yes, the printing does feel a little on the cheap side, but I appreciate the affordable price.
Don't waste your time with CLRS. This book is much much better. Yes it's concise and doesn't explain every detail, but that's what makes it good. It forces you to think about how each algorithm it cover works rather than spoon feed you into thinking or 'getting' each one in a particular way.
Great material on Graphs and associated Algorithms. This is not a traditional Data Structures book. Also, on a secondary note, Print and Paper quality is good and makes me feel like studying it.
More concise than Introduction to Algorithms, certainly, but not better. I often feel that the explanations given in Algorithms are much harder to grasp than those in the CLRS book. Partly, this is due to fewer pages devoted to each concept, and fewer concepts overall (leading to a spottier understanding of the field and the relations between concepts.) However, this is also partly due to what I feel is a more confusing writing and teaching style by the authors of Algorithms.Algorithms was the assigned text in a class here at UC Berkeley, and I feel I would have been very confused if I did not have CLRS to cross-reference and explain things more clearly, and in more detail.This text isn't bad, per se, but there are definitely better options. I've taken the class with Christos Papadimitriou, and even he has said that everyone should own CLRS. Given that, I'm not sure what purpose this text serves. Is brevity actually better if you end up spending more time trying to understand things?
Vazirani is the GOAT. This book reads like him whispering sultrily into your ear. It's actually a joy to read and doesn't "feel like a textbook." The book is surprisingly slim, and the chapters feel just as long as they need to be. He taught my Algorithms class, and a number of of our homework problems came from the exercises in this book.
A good text. Structured very nicely with lots of appropriate background that builds up the story and derivation of the algorithms. A bit too terse in places, leaving someone without a teacher hard-pressed to implement their efficient "selection" algorithm for medians or other percentiles into data sets, for instance. This situation happens a few critical times in the text. Although the coverage is good for the price and size of this volume, it really does lack in the amount of pseydocode listings as well. So, overall, good text on a budget and with a good professor, but kind of useless as a reference. Get the MIT press algorithms book if you need a reference text.
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