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TABLE OF CONTENTS16 sections

Data Mining and Feature Engineering

01Data Mining and Feature Engineering 02Foundations Of Data Mining And Knowledge Discovery 03Data Understanding Measurement And Exploratory Analysis 04Data Preparation And Quality Engineering 05Feature Engineering Foundations And Design Principles 06Engineering Features For Diverse Data Types 07Feature Selection Extraction And Dimensionality Reduction 08Supervised Data Mining Classification And Prediction 09Unsupervised Mining And Pattern Discovery 10Anomaly Detection Imbalanced Data And Rare Events 11Model And Feature Evaluation 12Interpretability Causality And Decision Analytics 13Scalable Pipelines Feature Stores And Mlops 14Data Mining Strategy And Organizational Applications 15Ethics Privacy Security And Governance 16Emerging Directions In Automated And Ai Assisted Feature Engin...

Chapter 11

Interpretability Causality And Decision Analytics

PREVIOUS SECTIONModel And Feature Evaluation UP NEXTScalable Pipelines Feature Stores And Mlops

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