No Kgnuggets tem uma lista bem interessante sobre as razões para ler Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
1. New case studies. Find detailed stories you have never before heard from Hewlett-Packard, Chase, and the Obama Campaign. And did you know that John Elder once invested all his own personal money into a blackbox stock market system of his own design? That’s the opening story of Chapter 1.
2. Complete conceptual coverage. Although packaged with catchy chapter titles, the conceptual outline is fundamental: 1) deployment, 2) civil liberties, 3) data, 4) core modeling, 5) ensemble models, 6) IBM’s Jeopardy!-playing Watson, and 7) uplift modeling (aka net lift or persuasion modeling).
3. A cross-industry compendium of 147 cases. This comprehensive collection of mini-case studies serves to illustrate just how wide the field’s reach extends. A color insert, it includes a table for each of the verticals: Personal Life, Marketing, Finance, Healthcare, Crime Fighting, Reliability Modeling, Government and Nonprofit, Human Language and Thought, and Human Resources. One reviewer said, “The tables alone are worth the price of admission.”
4. Privacy and other civil liberty concerns. The author’s treatise on predictive analytics’ ethical realm, a chapter entitled “With Power Comes Responsibility,” addresses the questions: In what ways does predictive analytics fuel the contentious flames surrounding data privacy, raising its already-high stakes? What civil liberty concerns arise beyond privacy per se? What about predictive crime models that help decide who stays in prison?