The Art of Randomness Cover

The Art of Randomness

Randomized Algorithms in the Real World
by Ronald T. Kneusel
January 2024, 400 pp.

Download Chapter 6: Computer Science Algorithms

Look Inside!

Art of Randomness back coverArt of Randomness pages 90-91Art of Randomness pages 142-143Art of Randomness pages 244-245

The Art of Randomness is a hands-on guide to mastering the many ways you can use randomized algorithms to solve real programming and scientific problems. You’ll learn how to use randomness to run simulations, hide information, design experiments, and even create art and music. All you need is some Python, basic high school math, and a roll of the dice.

Author Ronald T. Kneusel focuses on helping you build your intuition so that you’ll know when and how to use random processes to get things done. You’ll develop a randomness engine (a Python class that supplies random values from your chosen source), then explore how to leverage randomness to:

  • Simulate Darwinian evolution and optimize with swarm-based search algorithms
  • Design scientific experiments to produce more meaningful results by making them truly random
  • Implement machine learning algorithms like neural networks and random forests
  • Use Markov Chain Monte Carlo methods to sample from complex distributions
  • Hide information in audio files and images, generate art, and create music
  • Reconstruct original signals and images from only randomly sampled data

Scientific anecdotes and code examples throughout illustrate how randomness plays into areas like optimization, machine learning, and audio signals. End-of-chapter exercises encourage further exploration.

Whether you’re a programmer, scientist, engineer, mathematician, or artist, you’ll find The Art of Randomness to be your ticket to discovering the hidden power of applied randomness and the ways it can transform your approach to solving problems, from the technical to the artistic.

Author 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).

Table of contents 

Chapter 1: The Nature of Randomness
Chapter 2: Hiding Information
Chapter 3: Simulate the Real World
Chapter 4: Optimize the World
Chapter 5: Swarm Optimization
Chapter 6: Machine Learning
Chapter 7: Art
Chapter 8: Music
Chapter 9: Audio Signals
Chapter 10: Experimental Design
Chapter 11: Computer Science Algorithms
Chapter 12: Sampling

View the Copyright page
View the detailed Table of Contents
View the Index


"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

Extra Stuff 

Click here to download the online resources.