Churn Modling

This churn modeling project focuses on predicting customer churn using machine learning techniques. I applied data preprocessing, cross-validation, and built a K-Nearest Neighbors (KNN) model for classification. Key evaluations included confusion matrix analysis and detailed visualizations. I also discussed model performance and the impact of overfitting. The goal is to help businesses retain customers by identifying churn risk early.