Customer Churn Prediction Model

A machine learning solution that predicts customer churn with high accuracy. The project involved data cleaning, feature engineering, and training multiple classification models (Random Forest, XGBoost) to identify customers likely to leave. The final model achieved 85%+ accuracy, enabling proactive strategies to improve retention and reduce business losses.