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What is the difference between supervised and unsupervised learning?
Supervised learning trains on examples where the right answer is known, such as past sales or whether a customer churned, and learns to predict that answer for new data. Unsupervised learning has no answer column and instead looks for structure, such as grouping similar customers or finding unusual records.
Most business forecasting is supervised: you have historical outcomes and want to predict future ones. Regression predicts a number (next month's sales) and classification predicts a category (will this customer leave, yes or no).
Unsupervised methods such as clustering support segmentation and some anomaly detection. Because there is no correct answer to score against, judging them is more subjective, so results should be checked for usefulness with people who know the business.
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