You are working on a digital product and have user activity data from signups, sessions, and feature usage. The team wants both a model that predicts whether a user will convert and an analysis that groups users into meaningful behavioral segments for downstream product decisions.
How would you explain the difference between supervised and unsupervised learning in this setting, and how would you decide when to use each approach for the prediction task versus the segmentation task?
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