Supervised learning is a machine learning paradigm where input data is directly related to the output data in a training set. Supervised machine learning is used when you have pre-established and labelled data that can be used for training.
The main types of supervised learning problems are
Classification is used to predict categorical or discrete values, such as yes or no and dog, reptile or cat. The goal is to classify data points into one of several predefined classes based on their features.
Regression is used to predict continuous numerical values, such as temperature or stock prices. The goal is to create a mathematical model that can accurately predict an output value based on input features.