Classic Computer Science Problems in Python: Easy to advanced programming challenges to sharpen your coding skills and improve your algorithmic thinking - Brossura
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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 algorithms
- Common techniques for graphs
- Neural networks
- Genetic algorithms
- Adversarial search
- Uses type hints throughout
- Covers 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 problems
- Search problems
- Constraint-satisfaction problems
- Graph problems
- Genetic algorithms
- K-means clustering
- Fairly simple neural networks
- Adversarial search
- Miscellaneous problems
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sugli autori
David Kopec is an Assistant Professor of Computer Science & Innovation at Champlain College in Burlington, VT. He is an experienced iOS developer and the author of Dart for Absolute Beginners.
David Kopec is an Assistant Professor of Computer Science & Innovation at Champlain College in Burlington, VT. He is an experienced iOS developer and the author of Dart for Absolute Beginners.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Paperback. Condizione: New. Classic Computer Science Problems in Python presents dozens of coding challenges, ranging from simple tasks like finding items in a list with a binary sort algorithm to clustering data using k-means. Classic Computer Science Problems in Python deepens your Python language skills 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 Key Features · Breadth-first and depth-first search algorithms · Constraints satisfaction problems · Common techniques for graphs · Adversarial Search · Neural networks and genetic algorithms · Written for data engineers and scientists with experience using Python. For readers comfortable with the basics of Python About the technology Python is used everywhere for web applications, data munging, and powerful machine learning applications. Even problems that seem new or unique stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills, and you'll be ready to use Python for AI, data-centric programming, deep learning, and the other challenges you'll face as you grow your skill as a programmer. David Kopec teaches at Champlain College in Burlington, VT and is the author of Manning's Classic Computer Science Problemsin Swift. Codice articolo LU-9781617295980
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Paperback. Condizione: new. Paperback. Classic Computer Science Problems in Python presents dozens of coding challenges, ranging from simple tasks like finding items in a list with a binary sort algorithm to clustering data using k-means. Classic Computer Science Problems in Python deepens your Python language skills 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 Key Features Breadth-first and depth-first search algorithms Constraints satisfaction problems Common techniques for graphs Adversarial Search Neural networks and genetic algorithms Written for data engineers and scientists with experience using Python. For readers comfortable with the basics of Python About the technology Python is used everywhere for web applications, data munging, and powerful machine learning applications. Even problems that seem new or unique stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills, and youll be ready to use Python for AI, data-centric programming, deep learning, and the other challenges youll face as you grow your skill as a programmer. David Kopec teaches at Champlain College in Burlington, VT and is the author of Mannings Classic Computer Science Problemsin Swift. "For intermediate Python programmers"--Back cover. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781617295980
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