Welcome to “A Beginner's Guide to Machine Learning in JavaScript”! In this series, I'll teach the concepts behind machine learning using the ml5.js library.
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Can the unpredictable evolutionary and emergent properties of nature be captured in software? Can understanding the mathematical principles behind the physical world help to create digital worlds? This learning playlist focuses on the programming strategies and techniques behind computer simulations of natural systems. I'll explore topics ranging from basic mathematics and physics concepts to more advanced simulations of complex systems. Subjects covered include physics simulation, trigonometry, self-organization, genetic algorithms, and neural networks. This track accompanies https://natureofcode.com/
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Take a ride along the Pixels track and explore pixels with p5.js and Processing. In this track, I demonstrate how to work with real-time live video, using tint() to change colors and copy() to takes snapshots. I also explore how the pixel array works. I create examples of "software" mirrors that draw pixels as shapes or use DOM elements. I demonstrate how to create a "painting" with particles smearing colors from pixels, and build a slitscan effect.
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