Smart Customer Churn Prediction System

Built an end-to-end machine learning system using Python to predict customer churn based on behavioral and transactional data. The project includes data preprocessing, feature engineering, exploratory data analysis (EDA), model training, evaluation, and deployment-ready prediction workflows using libraries such as Pandas, Scikit-learn, Matplotlib, and Seaborn.