Vectorized K-Means Clustering (opens in new tab)

K-means clustering (previous discussion) is an unsupervised learning algorithm which assigns points to one of K different clusters based on the distance of that point to a centroid. The points may represent physical locations, or embeddings in high-dimensional vector space. 🌟Check out the demo (in two dimensions) below. Centroids are colored white.🌟 start Note that the points are changing color only, not moving. General algorithm The basic K-means algorithm is fairly simple and has two steps,...