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Graph Algorithms the Fun Way

Powerful Algorithms Decoded, Not Oversimplified

Jeremy Kubica author

Format:Paperback

Publisher:No Starch Press,US

Published:19th Nov '24

Should be back in stock very soon

Graph Algorithms the Fun Way cover

This book provides a fun and accessible introduction to graph algorithms, commonly used to solve a wide range of computational and mathematical problems. Full of humorous analogies, detailed diagrams, and real-world examples using the Python programming language, Graph Algorithms the Fun Way will show you how graph data structures can model a vast variety of phenomena - from physical mazes to communication networks - while helping you develop a strong foundation for how they work, when to use them, and how to create variants. It starts with the structure of graphs, demonstrating the ways they can represent connections between nodes, such as the best route through a city or how rumours spread in a social network. Each subsequent chapter introduces new graph algorithms along with their underlying concepts and applications - from basic searches to more advanced methods of exploring graphs. You'll have a blast solving brain-teasers including the 15-square puzzle, matching adopted pets with homes, calculating the maximum flow of a sewage network, traversing magical labyrinths, sorting recipe steps to craft the perfect cookies, and more. You'll also learn how to: Work with weighted and directed graphs, Use heuristics to prioritize which paths in a graph to explore, Determine which components of a graph are key for its structural integrity, Generate random mazes. Guided by the bestselling author of Data Structures the Fun Way, this equally fun follow-up will help you build a strong understanding of a crucial coding topic and apply graph algorithms to your own projects.

"Graphs may be the most natural data structure in the world. This comprehensive book unpacks the magic and mystery of many fascinating graph algorithms that enable powerful applications and insights from graphs."
—Kirk Borne, PhD, Chief Science Officer at DataPrime

ISBN: 9781718503861

Dimensions: unknown

Weight: unknown

264 pages