Customer Churn

This project focuses on identifying customers at risk of leaving a business using advanced data analytics and machine learning techniques. By analyzing historical customer behavior, transactional data, and engagement metrics, the model predicts potential churn with high accuracy. The insights generated allow businesses to implement targeted retention strategies, optimize marketing campaigns, and increase overall customer satisfaction. The project demonstrates end-to-end workflow skills, including data preprocessing, feature engineering, model selection, evaluation, and deployment of predictive models.