In this challenge, I demonstrate the entire process of training and deploying a machine learning classification model in JavaScript – data collection, model training, and prediction!
Challenges
Featured Challenge:
#11 — 3D Terrain Generation with Perlin Noise
Let's fly to new heights with a 3D terrain coding challenge! Using Perlin Noise and beginShape() + endShape() with triangle strips, I'll guide you through visualizing a 3D procedural terrain in Processing.
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Liven up your video calls with p5.js, ml5.js, Teachable Machine, and OBS Studio!
This challenge uses the pre-trained SketchRNN machine learning model (available with the ml5.js library) to create a p5.js sketch that finishes a person's drawing.
In this challenge, I attempt to create a Ukulele tuner in JavaScript using p5.js, ml5.js and the pre-trained machine learning model CREPE: A Convolutional REpresentation for Pitch Estimation. Can you make one with a more elegant and creative interface?
In this challenge, I attempt to make my own version of Google’s Dinosaur Game (T-Rex run!) with a unique twist – controlling the dinosaur (unicorn, in this case) with a machine learning Speech Commands model!
In this holiday coding challenge, I use ml5.js and Sketch-RNN to generate snowflake drawings.
