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Commodity Algorithms and Data Structures in C++: Simple and Useful

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Product details

Paperback: 619 pages

Publisher: CreateSpace Independent Publishing Platform (December 8, 2018)

Language: English

ISBN-10: 1987481577

ISBN-13: 978-1987481570

Product Dimensions:

8.3 x 1.4 x 11.7 inches

Shipping Weight: 4 pounds (View shipping rates and policies)

Average Customer Review:

3.2 out of 5 stars

6 customer reviews

Amazon Best Sellers Rank:

#1,036,026 in Books (See Top 100 in Books)

I teach Advanced C++. The code in “Commodity Algorithms and Data Structures in C++: Simple and Useful” is poorly written and confusing. I do make programing assignments from the book asking my students to study the code in “Commodity Algorithms and Data Structures in C++: Simple and Useful” and write correct C++ code.Two books are required for my Advanced C++ course:- “Data Structures and Algorithms in C++ 4th Edition” by Adam Drozdek- “The C++ Standard Library: A Tutorial and Reference” by Nicolai M. JosuttisI have also recommended these websites:GeeksForGeeksTechieDelight

This could have potentially been one of the best algorithmic books. It covers a wide variety of topics including some non standard (but non the less important) topics that are otherwise not covered in any other book. The bonus is that it contains well written modern c++ code. So why the 2 stars ? Because the author makes no attempts to explain the topics in fullness, or even partially.It seems that the author wanted to get the explanations part out of the way so he can code some more.The sentences are incomplete and instead the author uses mathematical notations. The Author assumes that the reader understands many subtleties in math and CS (which is for the most part incorrect) and skips those explanations as well. So, if you have the patience to figure out yourself what the code in this book does (based on the title of the chapter) then you'll enjoy it. Otherwise, like in my case this book will decorate the shelf.

This book gives implementation details for many algorithms with lots of practical advice. I thought my algorithm education was over in school, but after reading this I did realize that there is much I don't know. I am somewhat guilty to have skimmed over this rather quickly, and need to find some time to read properly. The comments sections are particularly helpful - in particular I have been putting off reading about Fibonacci heaps in Cormen, but after glancing at the heaps chapter comments here I figured that I don't have to because nobody uses Fib heaps, so I don't get why the Cormen book even bothers to devote a whole chapter to them. With this being self-published (createspace - ha!) the presentation is a bit rough (the author often uses logic symbols in plain sentences), but the book is nevertheless very readable.The machine learning stuff looks interesting. In particular, I have never seen machine learning code in C++. Books I read use R or Python or Java, but never C++, which I prefer. This doesn't seems like an introduction though, and I am happy to have read Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (Morgan Kaufmann Series in Data Management Systems) before this. I think the two books work well together because Witten is a good intro and this give a lot of details and explains implementation decisions. As minor thing, I do wish the author would cover deep networks rather than point to other books, but I am certainly going to take a look at those. Again, the comments useful and made me feel better about not really getting the whole "big data" thing - now I can tease my friends about it.

This book almost contains many different algorithms, which is very useful, especially to programmers. More importantly, it also contains implementation and readers should be able to read code to understand some details of the algorithm. The typesetting of the book may not look good enough but the content is great and certainly worth your time.If you want to improve both your understanding in algorithms and programming skills, this book should be the one you need; if you are looking for mathematical details of algorithms, for example proof, this book may not fit your needs but offers the basic definitions or detailed algorithm procedure, which can be helpful to your goal. You can take this book for reference when you need to implement some algorithms or when you want to learn new algorithms.

This short book is written in a somewhat unusual way. The cover is gorgeous, though I don't understand the bottom part. Exposition of all topics is very compact, but apparently complete and there is C++ code with almost every algorithm and data structure. Topic selection is also a bit unusual, for example I was hoping to see compact red-black tree code, but instead there is a one line mention of a study that found another tree data structure called treap superior to red-black tree along with detailed presentation of this data structure. I glanced at my copy of Knuth and saw that he plans to cover treap in his next edition, so maybe it is indeed a better choice.Also for a 200-something page book it covers very many topics. There are chapters on Monte Carlo and external memory algorithms which I have not seen in other books. As such this book seems to be offering an original approach rather than create another copycat of Knuth/Cormen. There are no exercises or questions for readers in this book, but I am considering using it for the algorithm's class I will teach this fall.There are specialized books for topics like machine learning and optimization, but this is the first book where I see clean C++ code for neural networks and the back-propagation math is somehow explained in one paragraph. Definitely a worthy addition to my computing book collection. Hopefully this one will force the Knuth/Cormen/Sedgewick/Weiss classics update their coverage.

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