Supervised Learning

Supervised learning is a foundational machine learning task where an algorithm learns to map input data to an output based on a dataset of labeled examples. The "supervision" comes from the fact that each input observation in the training data is paired with its correct or desired output label. The model's objective is to learn the underlying function that best describes this relationship between inputs and outputs, enabling it to make accurate predictions or classifications on new, unseen data that it has not encountered before.