Machine Learning Credit Default Prediction System

Design a sophisticated Python-based credit default prediction system using advanced machine learning techniques. The solution should integrate multiple data sources, implement feature engineering with techniques like polynomial features and interaction terms, use ensemble learning methods (stacking, blending), and generate probabilistic default risk scores. Create a modular pipeline that can be easily retrained, includes comprehensive model evaluation metrics, and interfaces with Google Sheets for reporting and tracking.