Classic Computer Science Problems in Python

Classic Computer Science Problems in Python is a book that provides coding challenges and exercises to deepen Python language skills. It covers breadth-first and depth-first search algorithms, constraints satisfaction problems, graphs, adversarial search, neural networks, and genetic algorithms. The book is written for data engineers and scientists with experience using Python and is designed to help readers master core skills for AI, data-centric programming, deep learning, and other programming challenges.

Format: Paperback / softback
Length: 224 pages
Publication date: 20 May 2019
Publisher: Manning Publications

Classic Computer Science Problems in Python presents a comprehensive collection of coding challenges, spanning from straightforward tasks such as locating items in a list using a binary sort algorithm to complex data clustering using k-means. This invaluable resource deepens your Python language proficiency by presenting you with time-tested scenarios, exercises, and algorithms. As you embark on a journey through examples encompassing search, clustering, graphs, and more, you will rediscover essential concepts and uncover timeless solutions to emerging problems.

Key Features:

Breadth-first and depth-first search algorithms: Explore these fundamental algorithms and their applications in solving complex problems.

Constraints satisfaction problems: Dive into the realm of solving problems with constraints, a fundamental aspect of computer science.

Common techniques for graphs: Gain expertise in navigating and analyzing graphs, a fundamental data structure in various domains.

Adversarial Search: Learn about this game-theoretic approach to solving optimization problems, which is particularly relevant in artificial intelligence and machine learning.

Neural networks and genetic algorithms: Explore these powerful tools for modeling and solving complex problems, drawing inspiration from biological systems.

Written for data engineers and scientists with experience using Python: This book is tailored to individuals who possess a solid foundation in Python and are eager to advance their skills in data engineering, scientific computing, and machine learning.

For readers comfortable with the basics of Python: This book assumes a basic understanding of Python syntax and concepts, making it an ideal starting point for those seeking to delve deeper into computer science and Python applications.

About the Technology:

Python, a versatile and powerful language, finds widespread application in web applications, data manipulation, and advanced machine learning applications. Even seemingly novel problems can be traced back to the foundations of classic algorithms, coding techniques, and engineering principles. By mastering these core skills, you will be well-equipped to leverage Python for AI, data-centric programming, deep learning, and the myriad challenges that lie ahead as you continue to expand your programming expertise.

David Kopec, an esteemed instructor at Champlain College in Burlington, VT, is the author of Mannings Classic Computer Science Problems in Swift. His extensive experience and expertise in computer science make him a trusted guide in this field.

By embarking on this journey through Classic Computer Science Problems in Python, you will not only enhance your Python language skills but also gain a deep understanding of fundamental computer science concepts and their practical applications. Prepare to unlock the full potential of Python and embark on a rewarding career in data engineering, scientific computing, and machine learning.

Weight: 436g
Dimension: 187 x 233 x 17 (mm)
ISBN-13: 9781617295980