Supervised Learning
Supervised learning is a type of machine learning where an algorithm learns from labeled training data in order to make predictions or decisions. The algorithm is trained on a dataset that includes input-output pairs, with the goal of learning a mapping function that can accurately predict the output for new, unseen input data. This type of learning is guided by a supervisor or teacher, who provides feedback to the algorithm during training to help it improve its predictions. Supervised learning is commonly used in tasks such as classification, regression, and anomaly detection.