July 30, 2011
Free Ebook Algorithms (4th Edition)
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Algorithms (4th Edition)
Free Ebook Algorithms (4th Edition)
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About the Author
Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science. He has held visiting research positions at Xerox PARC, Institute for Defense Analyses, and INRIA, and is member of the board of directors of Adobe Systems. Professor Sedgewick’s research interests include analytic combinatorics, design and analysis of data structures and algorithms, and program visualization. His landmark book, Algorithms, now in its fourth edition, has appeared in numerous versions and languages over the past thirty years. In addition, with Kevin Wayne, he is the coauthor of the highly acclaimed textbook, Introduction to Programming in Java: An Interdisciplinary Approach (Addison-Wesley, 2008). Kevin Wayne is the Phillip Y. Goldman Senior Lecturer in Computer Science at Princeton University, where he has been teaching since 1998. He received a Ph.D. in operations research and industrial engineering from Cornell University. His research interests include the design, analysis, and implementation of algorithms, especially for graphs and discrete optimization. With Robert Sedgewick, he is the coauthor of the highly acclaimed textbook, Introduction to Programming in Java: An Interdisciplinary Approach (Addison-Wesley, 2008).
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Product details
Hardcover: 976 pages
Publisher: Addison-Wesley Professional; 4th edition (March 19, 2011)
Language: English
ISBN-10: 032157351X
ISBN-13: 978-0321573513
Product Dimensions:
7.8 x 1.5 x 9.4 inches
Shipping Weight: 3 pounds (View shipping rates and policies)
Average Customer Review:
4.5 out of 5 stars
219 customer reviews
Amazon Best Sellers Rank:
#29,002 in Books (See Top 100 in Books)
This book has been a fantastic supplement to my learning while taking my first Algorithms course in college. Sedgewick and Wayne show detailed step-by-step explanations of recursive calls, data-structures being built, etc. My class textbook is Algorithm Design which is extremely dense and can be exhausting to read. Whenever I'm not understanding something from that book I hop on over to this one, read the same topic with much more explanations, and it becomes clear. This book also implements everything in Java, and since my school's primary language is Java it helps me have a stronger grasp of actual implementations and helps me link algorithms and data-structures to my actual projects. There's also lots of supplemented material with this book such as Coursera and their booksite. Recommend it for everyone!
Well written and well organized covers all of the important algorithms. I have Robert Sedgewick's two prior books Algorithms in C. This book is much easier to understand and present much simpler manner. I bought this as way of preparing for interviews and it is helping me a lot. At the end of the day It is not hard to impress Google. Amazon and FB engineers at interviews when you are well prepared.
More beginner-friendly than some of the other popular algorithms textbooks. It doesn't crush the reader with proofs or some weird pseudocode language. It doesn't rely on having much math knowledge. It uses laudably-simple Java. The exercises are great. The diagrams are great. There are videos on Coursera if you want verbal explanations too. Doesn't get hung-up on esoteric theory terminology. Contains all the algorithms and datastructures for most job interviews. To build some advanced algorithmic software, this is not your reference; it is too basic. As a bonus, there are great hints about software design practice sprinkled through the book as they are relevant.
The book itself is outstanding. IMO, this is the best textbook for students who really want to learn "algorithms" regarding implementation and its analysis. Compared to CLRS, Sedgewick's approach is more accessible and takes more care about how an algorithm is actually implemented. Besides, the booksite and the course in Coursera, especially the programming assignments and quiz, are extremely useful. Other aspects of the books including algorithm design (OOP), coding style and comment are very good. Readers not only study about algorithms but also about software engineering. I think the algorithms reading roadmap is: Algorithms (Sedgewick) -> CLRS -> Introduction to Analysis of Algorithms -> TAoCP.However, the huge problem which makes me voting 4 star for the book is that some figures and illustrates are rendered badly (page 9, 675, 624, 621, 579, 576, 346, 326). Although I requested Amazon a replacement, the new book still has the same issue.
For beginners, this book is a nice guide to algorithm compared with others like Introduction to Algorithm. The range of algorithms and data structures covered in the book is reasonable so you won't find your study like an endless journey. The algorithms have been implemented in Java so they could be tested to verify the result. This is much better than staring at pseudo code and trying to figure out how to implement yourself. Also the amount of text covering mathematical proof is limited, and you won't find it difficult to skip them.
Just got the Kindle version of the book today. The images are blurry, and this is disappointing because the book, so far, is well-written and informative. If there were a better Kindle version then I would be inclined to give this 4-5 stars based on what I have read so far. For nearly $60, I expect better ina Kindle version of a textbook. Can I get a discount when a better Kindle version comes out?
It has an excellent helper website that allows you to download most of the example code from the book and a few java helper classes to make reading and writing to files, stdout, and stdin quick and easy. It has a few helper classes like the run-time stopwatch all available for downloading.Some of the explanations and code examples were a little overly complicated- Sorting was explained using a 15-20 letter phase instead of starting with a single word to make it easier to digest and them moving on to the more complex example. On most topics our prof explained the algorithms a little differently than the book and his way was easier to comprehend.
Excellent book. Approachable, well-organized and also supported by a top notch website and course on Coursera.If you're new to the study of algorithms, the trio of this book, its website, and the Coursera course are a potent combination for successful learning.This is a more approachable alternative to the CLRS algorithms book.
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