This project involves building predictive models to analyze customer churn using Python, pandas, scikit-learn, and XGBoost. It includes data preprocessing, feature engineering, model training, and evaluation.
/data: Contains raw and processed datasets. Raw data should not be committed./notebooks: Jupyter notebooks for exploratory data analysis and prototyping./src: Python scripts for data processing, modeling, and evaluation./models: Saved model artifacts./reports: Generated reports and visualizations.