Gadgets

The Art of Randomness

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Described by its publishers, No Starch Press, as “a hands-on guide to mastering the many ways you can use randomised algorithms to solve real programming and scientific problems”, they write:

“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.”

Randomness

Scientific anecdotes and code examples are used to illustrate how randomness is related to areas such as machine learning, optimisation, and audio signals.

Written by Ronald T. Kneusel, it includes developing a Python-based randomness engine and then exploring how to use randomness to:

Simulate Darwinian evolution and optimise 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

You can read more about the book on the No Starch website.

As a taster you can also read a sample chapter online, dealing with computer science algorithms, starting with the Las Vegas and Monte Carlo randomised algorithms.

Author

Ronald T. Kneusel is a computer scientist who is an expert in machine learning. He has been working with ML in industry since 2003 and completed a PhD in machine learning from the University of Colorado, Boulder, in 2016.

Kneusel is also 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).