Interpretable Spam Filters¶
This project develops a predictive model to make classification of emails as spam or non-spam. The model was trained on a dataset provided by University of California Irvine Machine Learning Repository. Our pipeline includes exploratory data analysis, hyperparameter tuning, model selection and model interpretation parts.
The code in this project is commited by Utku Can Ozturk and Cornelia Gruber.