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This is the second in a 4-part series where Anders Larson and Shea Parkes discuss predictive analytics with high cardinality features.  In this episode they focus on y-aware feature engineering.  Y-aware feature engineering is all about carefully bleeding information from your training response back into your engineered features without grossly misrepresenting your ability to generalize to new data.