CustomerChurnPrediction

The project focuses on predicting customer churn, which is the phenomenon where customers stop using a product or service. This project combines machine learning techniques such as Logistic Regression, Random Forest, k-Nearest Neighbors,AdaBoost and XGBClassifier. Integrated privacy techniques such as PATE and Federated Learning to protect sensitive customer data while achieving robust predictive performance.