Email Spam Detection System Using Natural Language Processing

This project aims to design an intelligent spam detection system that automatically classifies emails as spam or legitimate using Natural Language Processing and machine learning algorithms, improving email security and user productivity.

Collect labeled email datasets Preprocess text using NLP techniques Perform tokenization, stop-word removal, and stemming Convert text data into numerical features Train classifiers such as Naive Bayes and SVM Evaluate accuracy and confusion matrix Build a spam classification module Develop a simple email input interface Display classification results with confidence score Test system against real email samples Document methodology and performance results