The Art of Randomness :Randomized Algorithms in the Real World
The Art of Randomness :Randomized Algorithms in the Real World
paperback
Published:
5 March, 2024
paperback
Published:
5 March, 2024
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Description
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.
More Details
| Type | Book |
|---|---|
| ISBN13 | 9781718503243 |
| ISBN10 | 1718503245 |
| Number Of Pages | 400 |
| Item Weight | 1000 g |
| Publisher / Reseller | No Starch Press,US |
| Format | paperback |
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Media Reviews
"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
GoodReads Reviews
Author's Bio
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).