Classic Computer Science Problems in Python: Easy to Advanced Programming Challenges to Sharpen Your Coding Skills and Improve Your Algorithmic Thinking - Tapa blanda
Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
David Kopec teaches at Champlain College in Burlington, VT and is the author of Manning’s Classic Computer Science Problems in Swift.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Classic Computer Science Problems in Python
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Paperback. Condición: 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. Nº de ref. del artículo: LU-9781617295980
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Paperback. Condición: 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. Nº de ref. del artículo: 9781617295980
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Classic Computer Science Problems in Python
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ISBN 10: 1617295981
ISBN 13: 9781617295980
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