K-means
Software / App
K-means is an unsupervised learning algorithm used for clustering. It partitions data points into K distinct clusters based on their proximity to the cluster centroids, using a hard assignment approach where each point belongs to exactly one cluster.
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Videos Mentioning K-means
Stanford CS229 Machine Learning | Spring 2026 | Lecture 10: GMM (EM), PCA
Stanford Online
K-means is an unsupervised learning algorithm used for clustering. It partitions data points into K distinct clusters based on their proximity to the cluster centroids, using a hard assignment approach where each point belongs to exactly one cluster.
Stanford CS229 Machine Learning | Spring 2026 | Lecture 9: K-Means and GMM (non-EM)
Stanford Online
An unsupervised learning algorithm used for clustering data points into K distinct groups.