What is the difference between supervised and unsupervised learning?

Question

Accepted Answer

Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data to find patterns.

Supervised learning requires a target variable to be predicted, while unsupervised learning does not.
Supervised learning algorithms include regression, classification, and decision trees, while unsupervised learning algorithms include clustering and association.
Examples of supervised learning include predicting housing prices based on features like location and square footage, while examples of unsupervised learning include identifying groups of customers with similar purchasing habits.

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