Machine Learning Feature Engineering Tracking Workbook

Design a comprehensive feature engineering tracking workbook for data science teams that automatically logs, scores, and evaluates potential machine learning model features. Implement dynamic scoring mechanisms that calculate feature importance, correlation coefficients, and potential predictive power using advanced statistical formulas. Create interactive visualization layers that help data scientists quickly understand feature interactions and eliminate low-value or redundant attributes.