Customer Churn Prediction
Developing an end-to-end supervised machine learning solution to predict customers at risk of churn using a telecom customer dataset. Performed business understanding, data profiling, cleaning, exploratory data analysis, statistical analysis, and feature engineering. Built a Logistic Regression baseline with categorical encoding and numerical feature scaling, then generated churn predictions and probability scores for unseen customers.