Answer / Raj Kapoor

Supervised learning is a type of machine learning where the algorithm learns to map inputs to outputs based on labeled training data. The goal is to learn a general function that can accurately predict the output for new, unseen inputs. Common supervised learning algorithms include linear regression, logistic regression, decision trees, support vector machines, and neural networks. These algorithms are trained on a dataset containing input features (x) and corresponding labels or outputs (y). The algorithm then learns to find patterns in the data that can be used to make predictions.

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