How Neural Networks Learn to See — Computer Vision Explained #Shorts

Añadido: 2026-05-17

[00:00:01]K-means clustering automatically groups similar data points together, like sorting M&M's by color. The algorithm places three centroids randomly, then iterates. Points join nearest centroid, centroids move to group centers. Quick question, what happens when centroids stop moving in K-means clustering? Correct. When centroids stop moving, the clusters have converged to their final optimal positions.