Five Reasons Siegel's Book "Predictive Analytics" Matters to Experts

My new book — Predictive  Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die  — is a revealing, accessible primer positioned to appeal well outside our industry.
But, if you’re already an expert, here are five reasons to read it nonetheless:

  1. New detailed case studies
  2. Advanced topics (ensembles, uplift, etc.)
  3. An in-depth, startling treatise on privacy
  4. A compendium of 147 mini-case studies
  5. A means to share your field with your family, friends, or  supervisor

I took on a rewarding challenge: sharing with layreaders at  large a complete picture of predictive analytics, from the  way in which it serves actionable value to organizations, down to      the inner workings of predictive modeling. It’s high time the predictive power of data — and how to analytically tap it — be demystified to reveal its intuitive yet awe–inspiring nature. As you and I know, learning from data to predict human behavior is not arcane. Rather, it is a broadly applicable no–brainer. If we  spread the word with an appropriately friendly overview, we’ll readily earn broad buy in, much to the benefit of our blossoming  industry.

More than a string of anecdotes, this book delivers complete   conceptual coverage of the field and places predictive analytics into a worldview perspective, defining its societal and even      cultural context. Although packaged with catchy chapter titles and brand name stories, the conceptual outline is fundamental: 1) deployment, 2) civil liberties, 3) data, 4) core modeling, 5) ensembles, 6) IBM’s Watson, and 7) uplift modeling (aka net lift or persuasion modeling).

Although this pop science, mathless introduction is readable by everyone, you as an expert will also benefit from reading it. While some endorsers proclaim it is “The Freakonomics of big data”    that “reads like a thriller!”, others speak to the    practitioner:

“The definitive book of this industry has arrived. Dr.  Siegel has achieved what few have even attempted: an  accessible, captivating tome on predictive analytics that is a  ‘must read’ for all interested in its potential — and peril.” —Mark Berry, VP, People Insights, ConAgra Foods

“Written in a lively language, full of great quotes,  real-world examples, and case studies, it is a pleasure to  read. The more technical audience will enjoy chapters on The          Ensemble Effect and uplift modeling — both very hot trends. I highly recommend this book!” —Gregory Piatetsky-Shapiro, Editor, KDnuggets; Founder, KDD          Conferences

Here’s a bit more on the five reasons this book matters to you:

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. Advanced topics. Dive into ensemble models, crowdsourcing predictive analytics, uplift modeling (aka net lift or persuasion modeling), text analytics, and social media-based financial indicators. Plus, enjoy a fun yet fairly deep chapter on IBM’s Jeopardy!-playing Watson computer.

3. Privacy and other civil liberty concerns. This ethical realm is so intractable and inconstant, no one is a true expert, in a sense. My treatise on it, 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?

4. 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. This color insert 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 PhD-level technical book reviewer complimented me by saying, “The tables alone are worth the price of admission.”

5. Share your field of expertise. Would you like your colleagues and manager to better understand the value and potential of your work? Would you enjoy seeing your loved ones        not only learn what the heck it is you do and why it’s so  important, but enjoy it and get excited? Give this book to your  family, friends, and boss.

Author Bio        

Eric Siegel, Ph.D., founder of Predictive Analytics World  and Text Analytics World, and Executive Editor of the Predictive  Analytics Times, makes the how and why of predictive analytics      understandable and captivating. In addition to being the author of   Predictive Analytics: The Power to Predict Who Will Click, Buy,  Lie, or Die, Eric is a former Columbia University professor      who used to sing to his students, and a renowned speaker, educator  and leader in the field.

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