Classic Computer Science Problems in Python

November 2, 2019 - Comment

Summary 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! Purchase of

Summary

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!

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

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

Search algorithmsCommon techniques for graphsNeural networksGenetic algorithmsAdversarial searchUses type hints throughoutCovers Python 3.7

About the Reader

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 Beginne (Apress, 2014) and Classic Computer Science Problems in Swift (Manning, 2018).

Table of Contents

Small problemsSearch problemsConstraint-satisfaction problemsGraph problemsGenetic algorithmsK-means clusteringFairly simple neural networksAdversarial searchMiscellaneous problems

Comments

Anonymous says:

Best CS book I’ve bought in years I absolutely love Classic Computer Science Problems in Python. It taught me both how to use Python in ways I never had before and about some computer science concepts that I may have heard of but had never used for actual coding projects. The book presents a large amount of information in a surprisingly small number of pages. I appreciate that the description of the material is to-the-point and not mathematical. This is the only computer science book I’ve read cover-to-cover in probably ten…

Anonymous says:

Lacks depth Author dives right into coding generic frameworks without first explaining a problem in depth. Explanation does follow the code but is usually quite superficial. No complexity analysis for the algorithms.Book is not bad at all overall, but could be much better had it proper structuring and more in-depth exploration of the problems/algorithms in question.

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