Supervised learning

As the name specifies, supervised learning means that the presence of supervisor is required to perform the task. Generally, the machine is trained by using the collected data which is well labelled and is known as labelled data, so that supervised learning algorithm can analyse the training data and give correct outcome using labelled data. The algorithm used in the working of supervised learning is shown in Figure 1.2.

Supervised learning is divided into two categories: regression and classification.

Regression is a technique which is used to find the relation between independent and dependent variables. Classification is the process of dividing the data into specific and distinct class where we assign a label to each class. The working model of classification supervised learning is given in Figure 1.3.