Various types of supervised learning include: Classification: It is a Supervised Learning task in which the output is labeled (discrete value).  Output – Purchased has defined labels of 0 or 1; 1 indicates that the consumer will purchase, while 0 indicates that the customer will not. The purpose is to anticipate discrete values that correspond to a specific class and evaluate them based on their accuracy. There are two types of classification: binary and multi-class. The model predicts either 0 or 1; yes or no in binary classification; however, in multi-class classification, the model predicts more than one class. Regression: It is a Supervised Learning assignment with a continuous value output.