We will only explore an easy model, Logistic Regression. Logistic Regression is a supervised machine learning algorithm for classification problems. 

It is used to predict a binary outcome (1 / 0, Yes / No, True / False) given a set of independent variables. The algorithm builds a model that assigns a probability to each outcome and makes a prediction based on which outcome has the highest probability. 

The model is represented by a logistic function that maps the input variables to a probability between 0 and 1. Logistic Regression can be used for binary classification, but it can also be extended to multi-class classification by training multiple binary classifiers and combining their results. Logistic Regression is widely used in various fields, including medical research, marketing, and social sciences.

In this project, we are going to classify spam email according to their content.