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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This track is a compilation of the many Snowflakes challenges that I have done during my annual fundraiser for the Processing Foundation. Donations can be made at https://processing.org/donate/. Thank you!
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In these videos I demonstrate how to train image and sound classification machine learning models and deploy those models to a web application using the p5.js and ml5.js JavaScript libraries.
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This side track is a collection of coding challenges for various (classic and new) video games in Processing (Java) or JavaScript with p5.js.
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Folder for archived videos
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