// ◇ Classical Machine Learning
k-Means Clustering
Alternates assigning points and recomputing centers to form k clusters.
K 均值聚类 1982 Beginner core
IN PLAIN WORDS
Place k centers, assign points to the nearest, move centers to the mean, repeat. IVF indexes and product quantization in vector databases rely on it.
Used in: Customer segmentation, IVF indexes, color quantization
TIMELINE · prerequisites → this → what builds on it
01Original paper
Least squares quantization in PCM
Lloyd et al. · IEEE Transactions on Information Theory · 1982
DOI ↗ ✓ Verified · Crossref API doi:10.1109/TIT.1982.1056489
02Where it sits
Learn the left column first; the right column builds on this one.
Learn first
- No prerequisites — a good starting point
Related:Principal Component Analysis (PCA)
Left: prerequisites · right: builds on this · dashed: related. Full map →
03Learning resources
Official docs, explainers, courses and reference code. All links checked.
04Where the course teaches it
On learning paths:Zero to Deep Learning
For AI / data
- Verification: verified, checked 2026-10-21.
- JSON: /api/learn/algorithms.json (id:
kmeans)