Classic Computer Science Problems in Swift: Essential Techniques for Practicing Programmers

Classic Computer Science Problems in Swift: Essential Techniques for Practicing Programmers by Kopec, David. paperback edition. ISBN: 9781617294891.

Summary Classic Computer Science Problems in Swift invites readers to invest their energy in some foundational techniques that have been proven to stand the test of time. Along the way theyll learn intermediate and advanced features of the Swift programming language, a worthwhile skill in its own right. About the Technology Dont just learn another language. Become a better programmer instead. Todays awesome iOS apps stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills in Swift, and youll be ready for AI, data-centric programming, machine learning, and the other development challenges that will define the next decade. About the Book Classic Computer Science Problems in Swift deepens your Swift language skills by exploring foundational coding techniques and algorithms. As you work through examples in search, clustering, graphs, and more, youll remember important things youve forgotten and discover classic solutions to your "new" problems. Youll appreciate author David Kopecs amazing ability to connect the core disciplines of computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview! Whats Inside Breadth-first, depth-first, and A* search algorithms Constraint-satisfaction problems Solving problems with graph algorithms Neural networks, genetic algorithms, and more All examples written in Swift 4.1 About the Reader For readers comfortable with the basics of Swift. About the Author David Kopec is an assistant professor of computer science and innovation at Champlain College in Burlington, Vermont. He is an experienced iOS developer and the author of Dart for Absolute Beginners. Table of Contents Small problems Search problems Constraint-satisfaction problems Graph problems Genetic algorithms K-means clustering Fairly simple neural networks Miscellaneous problems