Here’s a very simple toy demonstration of how K-Means works that I made for fun years ago while studying machine learning: https://k-means.stackblitz.io/
Essentially K-Means is a way of “learning” categories or other kinds of groupings within an unlabeled dataset, without any fancy deep learning. It’s handy for its simplicity and speed.
The demo works with simple 2D coordinates for illustrative purposes but the technique works with any number of dimensions.
Note that there may be some things I got wrong with the implementation and that there are other variations of the algorithm surely, but it still captures the basic idea well enough for an intro.
Essentially K-Means is a way of “learning” categories or other kinds of groupings within an unlabeled dataset, without any fancy deep learning. It’s handy for its simplicity and speed.
The demo works with simple 2D coordinates for illustrative purposes but the technique works with any number of dimensions.
Note that there may be some things I got wrong with the implementation and that there are other variations of the algorithm surely, but it still captures the basic idea well enough for an intro.