Bad Choices: How Algorithms Can Help You Think Smarter and Live Happier

Almossawi, Ali

ISBN 10: 147365078X / ISBN 13: 9781473650787

Published by John Murray, 2018

About this Item

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Bibliographic Details

• Title: Bad Choices: How Algorithms Can Help You Think Smarter and Live Happier
• Publisher: John Murray
• Publication Date: 2018
• Language: English
• ISBN 10: 147365078X
• ISBN 13: 9781473650787
• Binding: Paperback
• Condition: Used; Very Good

About this title

Synopsis

A relatable, interactive, and funny exploration of algorithms, those essential building blocks of computer science - and of everyday life - from the author of the wildly popular Bad Arguments.

Algorithms -- processes that are made up of unambiguous steps and do something useful -- make up the very foundations of computer science. Yet, they also inform our choices in approaching everyday tasks, from managing a pile of clothes fresh out of the dryer to deciding what music to listen to.

With Bad Choices, Ali Almossawi, presents twelve scenes from everyday life that help demonstrate and demystify the fundamental algorithms that drive computer science, bringing these seemingly elusive concepts into the understandable realms of the everyday.

Readers will discover how:
· Matching socks can teach you about search and hash tables
· Planning trips to the store can demonstrate the value of stacks
· Deciding what music to listen to shows why link analysis is all-important
· Crafting a succinct Tweet draws on ideas from compression
· Making your way through a grocery list helps explain priority queues and traversing graphs
· And more

As you better understand algorithms, you'll also discover what makes a method faster and more efficient, helping you become a more nimble, creative problem-solver, ready to face new challenges. Bad Choices will open the world of algorithms to all readers making this a perennial go-to for fans of quirky, accessible science books.

About the Author

Ali Almossawi works on the Firefox team at Mozilla and is an alumnus of MIT's Engineering Systems Division (MS) and Carnegie Mellon's School of Computer Science (MS). Previous stints included working as a research associate at Harvard and as a collaborator at the MIT Media Lab. His writing has appeared in Wired and Scientific American.