Classic Computer Science Problems in Python

David Kopec (Autor)

Buch | Softcover

275 Seiten

2019
Manning Publications (Verlag)
978-1-61729-598-0 (ISBN)

Artikel merken

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.

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 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!

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.

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!

For readers comfortable with the basics of Python

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 Problems in Swift.

Erscheinungsdatum	08.11.2018
Verlagsort	New York
Sprache	englisch
Gewicht	429 g
Einbandart	kartoniert
Themenwelt	Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Informatik ► Web / Internet
Schlagworte	Algorithmen • Computer Science • Informatikstudium • Python
ISBN-10	1-61729-598-1 / 1617295981
ISBN-13	978-1-61729-598-0 / 9781617295980
Zustand	Neuware