Description
Spam emails are unwanted messages that contain advertisements, phishing links, or malicious content. These emails waste users’ time and may cause security risks. The purpose of this project is to develop a Machine Learning based system that automatically detects and classifies emails as spam or legitimate.
The system will use Natural Language Processing (NLP) techniques to analyze email text. A dataset of emails will be used to train machine learning algorithms such as Naïve Bayes or Logistic Regression. The model will learn patterns from spam and non-spam emails and predict whether a new email is spam.
The system will include features such as email text preprocessing, feature extraction, model training, and prediction. The final system will help users filter spam emails effectively and improve email security.