Gurjit S.

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Supervised learning is a type of machine learning where the model is trained using labeled data, meaning the correct answers are already provided. The model learns the relationship between inputs and outputs so it can make predictions on new data. For example, a model can learn to identify spam emails using emails that are already labeled as "spam" or "not spam." Unsupervised learning uses unlabeled data, where no correct answers are given. Instead of making predictions, the model analyzes the data to discover hidden patterns, similarities, or groups. For example, a business might use unsupervised learning to automatically group customers with similar purchasing behaviors for marketing purposes.

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