Answer Posted / Raj Bhupan Pandey

Supervised learning involves training a model on labeled data, where the correct answers are provided. The goal is to learn a mapping between inputs and outputs. Examples include classification and regression problems. In contrast, unsupervised learning deals with unlabeled data, meaning there are no pre-defined labels. The goal is to discover patterns or structure within the data, such as clustering or dimensionality reduction.

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