Python Natural Language Processing

Supervised learning

In this type of ML, we will provide a labeled dataset as input to the ML algorithm and our ML algorithm knows what is correct and what is not correct. Here, the ML algorithm learns mapping between the labels and data. It generates the ML model and then the generated ML model can be used to solve some given task.

Suppose we have some text data that has labels such as spam emails and non-spam emails. Each text stream of the dataset has either of these two labels. When we apply the supervised ML algorithm, it uses the labeled data and generates an ML model that predicts the label as spam or non-spam for the unseen text stream. This is an example of supervised learning.