When properly applied, randomness can be a powerful tool in programming, science, and art. This highly practical but geekily fun introduction to randomness shows you how to put chaos to work, illustrating its ability to power everything from the simulation of Darwinian evolution, to product placement in a grocery store, to hiding information in plain sight, and even how to generate art and music. By encouraging you to engage in 'what if' speculation, you'll build intuition about when and how to use randomness to get things done. Each chapter describes how randomness plays into the given topic area, then proceeds to demonstrate its problem-solving role with hands-on experiments to work through using Python code. By the end of the book, you'll see why randomness belongs in every programmer's toolbox. Explore the mathematical background of randomness, use randomness for encrypting messages, creating models, and implementing swarm-intelligence or machine-learning algorithms, discover how randomness is used in programming applications, and apply it to your own work.
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TABLE OF CONTENTS...IntroductionChapter 1: The Nature of RandomnessChapter 2: Hiding InformationChapter 3: Simulate the Real WorldChapter 4: Optimize the WorldChapter 5: Swarm OptimizationChapter 6: Machine LearningChapter 7: ArtChapter 8: MusicChapter 9: Audio SignalsChapter 10: Experimental DesignChapter 11: Computer Science AlgorithmsChapter 12: SamplingResourcesIndex
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"The Art of Randomness is a useful reference and resource for anyone who needs to apply the power of randomized algorithms, including programmers, scientists, engineers, mathematicians, even artists and musicians...highly recommended."—Midwest Book Review
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Produktdetaljer

ISBN
9781718503243
Publisert
2024-03-05
Utgiver
Vendor
No Starch Press,US
Høyde
234 mm
Bredde
177 mm
Aldersnivå
G, 01
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
400

Forfatter

Om bidragsyterne

Ronald T. Kneusel is a computer scientist, an expert in machine learning, and a lover of fine craft beers. Kneusel has been working with machine learning in industry since 2003 and completed a PhD in machine learning from the University of Colorado, Boulder, in 2016. He’s the author of four other books with No Starch Press: How AI Works (2023), Strange Code (2022), Practical Deep Learning (2021), and Math for Deep Learning (2021).