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Chapter 16
Title Page
Foreword: Why Data Science?
Chapter 1: CRISP-DM: Data Mining Process
Chapter 2: Techstack: The Technology Stack
Chapter 3: Visualization: Theory and Dashboard Design
Chapter 4: Tableau: Core Features
Chapter 5: Tableau: Calculations and Clustering
Chapter 6: Tableau: JavaScript API
Chapter 7: Excel: Bivariate Relationships
Chapter 8: Excel: Multivariate Prediction
Chapter 9: ML Studio: Introduction
Chapter 10: ML Studio: Selecting and Engineering Features
Chapter 11: ML Studio: Selecting and Optimizing the Algorithm
Chapter 12: Optimizing Model Fit: An Overview
Chapter 13: ML Studio: Text Analytics
Chapter 14: ML Studio: Matchbox Recommender
Chapter 15: ML Studio: Anomaly Detection
Chapter 16: ML Studio: Clustering
Chapter 17: Privacy: Information Privacy
Chapter 18: Project: Putting It All Together
Supplement: Reading Data with SQL
Supplement: Machine Learning
Supplement: Other Useful Azure Pills
Supplement: Python Data Analytics
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16.1
Clustering
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