Customer Churn Prediction

Customer Churn Prediction

Developed a Machine Learning classification project to predict customer churn based on customer demographics, subscription details, billing information, and support activity.

The project includes data preprocessing, exploratory analysis, categorical encoding, feature scaling, model training, and evaluation using Logistic Regression and Random Forest.

The solution provides a churn-risk signal that can help businesses identify customers who may leave and prioritize retention strategies.