Classic Computer Science Problems in Python

About this book

Highly recommended to everyone interested in deepening their understanding of Python and practical computer science. Key Features Master formal techniques taught in college computer science classes Connect computer science theory to real-world applications data and performance Prepare for programmer interviews Recognize the core ideas behind most new challenges Covers Python 3.7 Note: Purchase of the print book includes a free eBook in PDF Kindle and ePub formats from Manning Publications. About The Book Programming problems that seem new or unique are usually rooted in well-known engineering principles. Classic Computer Science Problems in Python guides you through time-tested scenarios exercises and algorithms that will prepare you for the new problems youll face when you start your next project. In this amazing book youll tackle dozens of coding challenges ranging from simple tasks like binary search algorithms to clustering data using k-means. As you work through examples for web development machine learning and more youll remember important things youve forgotten and discover classic solutions that will save you hours of time. What You Will Learn Search algorithms Common techniques for graphs Neural networks Genetic algorithms Adversarial search Uses type hints throughout This Book Is Written For For intermediate Python programmers. About The Author David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington Vermont. He is the author of Dart for Absolute Beginners (Apress 2014) Classic Computer Science Problems in Swift (Manning 2018) and Classic Computer Science Problems in Java (Manning 2020) Table of Contents 1. Small problems 2. Search problems 3. Constraint-satisfaction problems 4. Graph problems 5. Genetic algorithms 6. K-means clustering 7. Fairly simple neural networks 8. Adversarial search 9. Miscellaneous problems