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Classic Computer Science Problems in Swift: Essential Techniques for Practicing Programmers
Download Ebook Classic Computer Science Problems in Swift: Essential Techniques for Practicing Programmers
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Review
"A fun read to sharpen your classic programming skills and to bring your Swift programming to another level." --Becky Huett, Big Shovel Labs"An excellent book for all Swift programmers, and for students learning algorithms." --Julien Pohie, Dell"A hands-on and informative exploration of computer science problems."--Chad Johnston, Polaris Alpha "An extraordinary Swift language book and a contribution to the practice of Swift algorithmic problem solving." --Eric Giannini, Nexmo
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About the Author
David Kopec is an Assistant Professor of Computer Science & Innovation at Champlain College in Burlington, VT. He is an experienced iOS developer and the author of Dart for Absolute Beginners.
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Product details
Paperback: 224 pages
Publisher: Manning Publications; 1 edition (April 22, 2018)
Language: English
ISBN-10: 1617294896
ISBN-13: 978-1617294891
Product Dimensions:
7.2 x 0.5 x 7.5 inches
Shipping Weight: 13.4 ounces (View shipping rates and policies)
Average Customer Review:
4.1 out of 5 stars
5 customer reviews
Amazon Best Sellers Rank:
#112,660 in Books (See Top 100 in Books)
Do not fear. This is not a book heavy on theory. You will learn good programming practices and advanced Swift features in the context of solving classic CS problems. The author does a nice job of relating these problems to solving real-world business problems. The author provides clear straightforward explanations of these problems for those not familiar with them. This book also serves as a good refresher and provides insight into the inner workings of genetic and deep learning algorithms. There's a good blend of object-oriented, functional and protocol-oriented examples presented in the book. Building reusable framework code is reinforced throughout the book. There are numerous examples of advanced Swift features such as generics and protocol extensions. Playground code is provided for each chapter that is well-documented, easy to read and thoroughly explained in the book. This is not a Swift introductory book, as the author clearly states. You need good working knowledge of Swift in order to move through the material.
I mostly write Python, but this was a fun way to read some Swift and see how a Swift expert approaches some well known problems. This book was an easy read as it didn't got into the problems too deeply and could even be a bed time reader for the brave. I certainly couldn't write Swift after reading this, but it isn't a "learn Swift" book - I did feel much better about my ability to read and understand Swift after the book though. Not a bad addition to the bookshelf.
Overall I did enjoy reading this book but I feel it lacked depth.There are a lot interesting topics but none of them is covered with any relevant details. It is more about the code than the actual problems.I am not an expert Swift programmer but I was able to follow the code without too much problems.If would recommend this book for programmers that are already familiar with classic computer science problems and want to be exposed to more advanced Swift code.
If when you think "Switft" you picture Taylor this book is definitely not for you. However if you are a computer proframmer with real experience this book will prove to be both resource and a workbook. I liked that each chpter ended with exercised with which you cn check your competency. The writing is clear butthis is not beginner's mnual. It assumes an understanindg of Swift nd aassociated skills. That being said, it is solid.
A book good for both intermediate and experienced programmers who are interested in learning Swift. Even fairly new programmers will find this book helpful and a good starting point to be introduced to these classic problems. Anyone who takes an interest in Swift should find this book helpful. Chapter one focuses on problem solving techniques like recursion, simulation and memorization. Chapter 2 focuses on search problems and search algorithms. Chapter deals with building a framework that solves a range of problems that can be defined by variables of limited domains that have constraints between them. Chapter 4, 5, 6 and 7 get into graph algorithms, genetic algorithms, k-means clustering and neural networks. Final chapter covers miscellaneous problems that didn't fit anywhere else in the book. Good book for exploring coding techniques and algorithms.
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