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:
- New detailed case studies
- Advanced topics (ensembles, uplift, etc.)
- An in-depth, startling treatise on privacy
- A compendium of 147 mini-case studies
- 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.
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.
For more information please visit http://www.thepredictionbook.com