artlib.supervised
Supervised learning is a type of machine learning where a model is trained on labeled data, meaning that the input data is paired with the correct output. The goal is for the model to learn the relationship between inputs and outputs so it can make accurate predictions on new, unseen data. Supervised learning tasks can generally be categorized into two types: classification and regression.
Classification involves predicting discrete labels or categories, such as spam detection or image recognition. Regression, on the other hand, deals with predicting continuous values, like stock prices or temperature.