Overview The goal of this project is to build a machine learning model that can accurately classify emails into spam or ham categories. Logistic Regression is chosen for its simplicity and effectiveness in binary classification tasks.
Features Preprocesses email text data Extracts features from text using TF-IDF vectorization Trains a Logistic Regression model Evaluates the model's performance using accuracy, precision, recall, and F1-score