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ERIC SIEGEL, PhD, founder of Predictive Analytics World and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. Eric is a former Columbia University professorwho used to sing educational songs to his studentsand a renowned speaker, educator, and leader in the field.
Foreword Thomas H. Davenport xiii
Preface xv
What is the occupational hazard of predictive analytics?
Introduction: The Prediction Effect 1
Chapter 1: Liftoff! Prediction Takes Action (deployment) 17
Chapter 2: With Power Comes Responsibility: Hewlett-Packard, Target, and the Police Deduce Your Secrets (ethics) 37
Chapter 3: The Data Effect: A Glut at the End of the Rainbow (data) 67
Chapter 4: The Machine That Learns: A Look Inside Chase’s Prediction of Mortgage Risk (modeling) 103
Chapter 5: The Ensemble Effect: Netflix, Crowdsourcing, and Supercharging Prediction (ensembles) 133
Chapter 6: Watson and the Jeopardy! Challenge (question answering) 151
Chapter 7: Persuasion by the Numbers: How Telenor, U.S. Bank, and the Obama Campaign Engineered Influence (uplift) 187
Afterword 218
Ten Predictions for the First Hour of 2020
Appendices
A. Five Effects of Prediction 221
B. Twenty-One Applications of Predictive Analytics 222
C. Prediction People—Cast of "Characters" 225
Notes 228
Acknowledgments 290
About the Author 292
Index 293
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