I built a machine learning model to predict customer churn for a telecom company. Using Python, Pandas, and Scikit-learn, I cleaned and preprocessed customer data, applied feature engineering, and trained classification models such as Random Forest and XGBoost. The final model achieved over 85% accuracy and helped the company identify at-risk customers, enabling proactive retention strategies and reducing churn rates.
