INTRODUCTION : This project is a Spam Mail Prediction System that uses a Logistic Regression model to classify email messages as either spam or ham (non-spam). The system transforms raw email text data into numerical features using the TF-IDF vectorizer and then trains a Logistic Regression model on this data. The model is then used to make predictions about whether a given email is spam or ham.
mail_data.csv: Dataset containing email messages labeled as "spam" or "ham". main.ipynb: Python script implementing the spam mail prediction system. install
pip install numpy pandas scikit-learn