Email Spam Detection Using Logistic Regression

Most of the logistic regression theory is covered in this project.

Using these theories, We can identify whether emails are spam or not

Introduction

When we train the machine learning model we need to follow several steps.
While training this linear regression machine learning algorithm, we need to follow some steps to make the model accurate and fast. Amoung them are things like,

Data Collecting

Data Preprocessing

Data Analysis

Split the Data into training and testing

Evaluate the Model

Check model performance

Fine-tune the Model
A better understanding of these can be obtained from the following introduction and relative code sections related to the introduction can be obtained by observing the code.

We must collect the data we need according to our needs.
Depending on the target variable (dependent variable/ our predictor variable/ y) we need to collect other data (characteristics/ independent variables/ Features).

After collecting the data we need to clean it,

find missing data and fill them

Drop duplicate data

Turn categorical data into numerical or Boolean

Rename columns for easily understand

Separate target value and features
We can use Encoding method or dummy method for convert categorical data into numerical or boolean.

We can analyze the relationships between the target and the features using plots, graphs, etc.
We can identify the relationship through the following sample examples.