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Classic Computer Science Problems in Python

✍ Scribed by David Kopec


Publisher
Manning Publications
Year
2019
Tongue
English
Leaves
224
Edition
1
Category
Library

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No coin nor oath required. For personal study only.

✦ Synopsis


Classic Computer Science Problems in Python deepens your knowledge of problem-solving techniques from the realm of computer science by challenging you with time-tested scenarios, exercises, 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!

About the Technology
Computer science problems that seem new or unique are often rooted in classic algorithms, coding techniques, and engineering principles. And classic approaches are still the best way to solve them! Understanding these techniques in Python expands your potential for success in web development, data munging, machine learning, and more.

About the Book
Classic Computer Science Problems in Python sharpens your CS problem-solving skills with time-tested scenarios, exercises, and algorithms, using Python. You'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. You'll especially enjoy the feeling of satisfaction as you crack problems that connect computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!

What's Inside
β€’ Search algorithms
β€’ Common techniques for graphs
β€’ Neural networks
β€’ Genetic algorithms
β€’ Adversarial search
β€’ Uses type hints throughout
β€’ Covers Python 3.7

About the Reader
For intermediate Python programmers.

✦ 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

✦ Subjects


Algorithms; Genetic Algorithms; Neural Networks; Data Structures; Python; Classification; Clustering; Encryption; Graph Algorithms; Textbook; Version Control; Fibonacci Sequence; Memoization; Towers of Hanoi; Search Algorithms; Adversarial Search; Knapsack Problem; Traveling Salesman Problem


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