The 15-Day AI/ML Interview Bootcamp
Day 8 — k-means clustering and PCA, learning without labels
Unsupervised machine learning from scratch — Lloyd's k-means algorithm, k-means++ initialisation, choosing k with the elbow and silhouette, then principal component analysis by power iteration to compress and visualise data — with the clustering questions interviewers probe.
Product drops by your desk with a question that sounds simple: "What kinds of customers do we actually have?" You open the table. Forty thousand accounts, thirty-one columns each — orders a month, average basket, days since the last visit, share of purchases bought on sale, hour of day they browse. You scroll to the right looking for the column that says what kind of customer each row is. There isn't one. Nobody has ever written it down, and nobody is going to. Every model you've built since Day 1 started from an answer column. This table has none, and the interview version of the question is …
In this lesson
Unlock the rest of The 15-Day AI/ML Interview Bootcamp
Day 8 — k-means clustering and PCA, learning without labels is part of the full course. One payment unlocks every lesson, every other course, and every premium article — for life.