Classification Problems Supervised Machine Learning projects can be divided into regression and classification problems. In regression problems, we predict a continuous variable (e.g. temperature), while in classification, we classify the data into discrete classes (e.g. classify cat and dog images). A subset of classification problems is the so-called binary classification, where only two classes are considered. An example of this is classifying e-mails as spam and no-spam or cat images versus dog images.

Regression Problems Regression problems in Machine Learning are a type of supervised learning problem, where a continuous numerical variable is predicted, such as, for example, the age of a person or the price of a product. A special type is the Linear Regression, where a linear relationship between two (Simple Linear Regression or more (Multiple Linear Regression) is analyzed. The example plots in this article will be illustrated with a simple linear regression.