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Compare clustering methods: k-means, hierarchical, DBSCAN, and GMM.

k-means is the reflex answer, but it quietly assumes round, equal-size clusters and demands you know k upfront. The signal is positioning each alternative by the exact assumption it removes, and knowing when to reach for it.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

k-means is the reflex answer, but it quietly assumes round, equal-size clusters and demands you know k upfront. The signal is positioning each alternative by the exact assumption it removes, and knowing when to reach for it.

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