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We often hear that Machine Learning models learn patterns in data. But what does that actually look like in Geometry?If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data?In this scene we watch a Self-Organizing Map (SOM), a simple unsupervised neural model, learn the shape of a 3D datasets l, one static and the other dynamic. On top of this, we lay down a square grid of neurons whose weights live in the same plane.
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