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

Classic Computer Science Problems in Swift: Essential Techniques for Practicing Programmers
EPUB
  • eBook:
    Classic Computer Science Problems in Swift: Essential Techniques for Practicing Programmers
  • Author:
    David Kopec
  • Edition:
    1 edition
  • Categories:
  • Data:
    April 22, 2018
  • ISBN:
    1617294896
  • ISBN-13:
    9781617294891
  • Language:
    English
  • Pages:
    224 pages
  • Format:
    EPUB

Book Description
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 they'll learn intermediate and advanced features of the Swift programming language, a worthwhile skill in its own right.

About the Technology
Don't just learn another language. Become a better programmer instead. Today's awesome iOS apps stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills in Swift, and you'll 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, you'll remember important things you've forgotten and discover classic solutions to your "new" problems. You'll appreciate author David Kopec's 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!
What's 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

Content

Chapter 1. Small problems
Chapter 2. Search problems
Chapter 3. Constraint-satisfaction problems
Chapter 4. Graph problems
Chapter 5. Genetic algorithms
Chapter 6. K-means clustering
Chapter 7. Fairly simple neural networks
Chapter 8. Miscellaneous problems

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