Email Filtering System

This Python script demonstrates email spam classification using Logistic Regression & TF-IDF vectorization. It imports necessary libraries, preprocesses the data, trains a Logistic Regression model, and evaluates its accuracy on both training and testing data. Finally, it predicts whether a given email is spam or not.

Code Description

• Libraries: Numpy, Pandas, Scikit-learn
• Data: A CSV file containing email messages and their categories (spam/ham)
• Preprocessing: Conversion of text messages into numerical form using TF-IDF vectorization
• Model: Logistic Regression model is trained on the transformed features
• Evaluation: Accuracy scores are calculated for both training and testing data
• Prediction: The model predicts whether a given email message is spam or ham

Dependencies

• Numpy
• Pandas
• Scikit-learn