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Forbes's recommended reading list for the predictive analytics category.

Summary:

  • The Signal And The Noise: Why So Many Predictions Fail — but Some D... by Nate Silver. Nate Silver built an innovative system for predicting baseball performance and predicted the 2008 and 2012 elections within a hair’s breadth — all by the time he was thirty. The New York Times now publishes FiveThirtyEight.com, where Silver is one of the nation’s most influential political forecasters. Why read: This book will simultaneously inspire your “predictive” imagination and ground you in the realities of predictive analytics.
  • Predictive Analytics: The Power To Predict Who Will Click, Buy, Lie, or Die by Eric Siegel. Former Columbia University professor and Predictive Analytics World founder Eric Siegel has written a very accessible book on how predictive analytics works. It’s chock-full of dozens of real-world examples, such as how Chase Bank predicted mortgage risk (before the recession), IBM Watson won Jeopardy!, and Hewlett-Packard predicted employee flight risk. Why read: Predictive Analyticsis a perfectly paced explanation of how predictive analytics works and a repository of dozens of real examples across many use cases.

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