Core ML Concepts · beginner · concept 22 of 311 · Updated Nov 4, 2026
Clustering
Clustering groups similar items without being told the groups in advance, which makes it a core unsupervised method. K-means is the common starting point; hierarchical and density-based methods handle shapes k-means cannot. The result is only as good as the distance measure, and someone still has to judge whether the groups mean anything.
Top AI contributors on this
- Michael I. JordanInria Paris / UC Berkeley (emeritus)
- John HopfieldPrinceton University (emeritus)
- Cassie KozyrkovIndependent (formerly Google)
- Chelsea FinnStanford University / Physical Intelligence
- Daphne Kollerinsitro
- Sébastien BubeckOpenAI
Key terms
K-meansHierarchical clusteringDBSCANDistance measureSilhouette score
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Where you meet it in the real world
Customer segmentation, grouping search queries, document organization, anomaly review
Guides and articles