Regression and Classification are the main two types of supervised machine learning algorithms. The main difference between classification and regression is that, regression predicts the continuous output and classification predicts the discrete output values. You can think of predicting if a person has diabetics or not as a classification problem and predicting the oil price as a regression problem. Regression is useful when you want to estimate a continuous output value using a set of predictors (inputs) . Here we will see how we can implement linear regression using python and scikit-learn with the help of Advertisement dataset.