"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer
"The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com
Award-winning | Used by over 30 universities | Translated into 9 languages
An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques.
Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die.
Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections.
How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.
Predictive Analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.
In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction:
- What type of mortgage risk Chase Bank predicted before the recession.
- Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves.
- Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights.
- Five reasons why organizations predict death — including one health insurance company.
- How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual.
- Why the NSA wants all your data: machine learning supercomputers to fight terrorism.
- How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy!
- How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job.
- How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison.
- 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more.
How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more.
A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.
- Amazon Sales Rank: #13719 in Books
- Published on: 2016-01-11
- Original language:
- Number of items: 1
- Dimensions: 8.80" h x
1.10" w x
- Binding: Paperback
- 368 pages
From the Back Cover
TRANSLATED INTO 9 LANGUAGES USED IN COURSES AT MORE THAN 30 UNIVERSITIES
In this rich, fascinating—and surprisingly accessible—introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day.
Trendsetters like Chase, Facebook, Google, HP, IBM, Match.com, Netflix, the NSA, Pfizer, Target, and Uber are seizing upon the power of big data to predict human behavior—including yours.
Why? Predictive analytics reinvents industries and runs the world. Read on to discover how it combats risk, boosts sales, fortifies healthcare, optimizes social networks, toughens crime fighting, and wins elections.
"What Nate Silver did for poker and politics, this does for everything else."
—David Leinweber, author of Nerds on Wall Street
"The Freakonomics of big data."
—Stein Kretsinger, founding executive, Advertising.com
"A deeply informative dive into a topic that is critical to virtually every sector of business today."
—Geoffrey Moore, author of Crossing the Chasm
"Moneyball for business, government, and healthcare."
—Jim Sterne, founder, eMetrics Summit
Learn more: www.ThePredictionBook.com
About the Author
ERIC SIEGEL, PhD, is the founder of Predictive Analytics World and executive editor of The Predictive Analytics Times. A former Columbia University professor, he is a renowned speaker, educator, and leader in the field.
Most helpful customer reviews
3 of 3 people found the following review helpful.
By Anita Raquel
As time has gone by, I've found myself going back again and again to refer to specific points discussed in this book. It was a bit heavy at first, thick with facts that I found irritating and contradictory to certain favorite and closely held biases of mine, but over time, I could see his points better and better, in spite of myself.
Life isn't fair, and people certainly aren't. The ways that they react to things reflects this to a degree that would surprise even the coldest eyed cynic, and there it is- the thing that bothered me so much....but it's best if you face it. There are some pleasant discoveries in here too, but I think the most important aspect is illusion busting. Those sweet daydreams about how things should be, might be exactly what is holding you back.
Forewarned is forearmed, and the information in here is of a hefty caliber. Use it well.
Yes, I did actually buy this book, and it was worth every penny.
2 of 2 people found the following review helpful.
This book is a great overview for anyone who is interested in applying Predictive Analytics.
As a professional with extensive operations & development background I wish I could have read this book when I began my journey into Data Science. I am someone who has used and built traditional business intelligence tools over the last fifteen years this book is fantastic at framing how Predictive Analytics is being used and for what specific business benefits.
The book is intentionally not filled with math formulas (which may turn off some) but it focuses more on use cases of how the businesses around you are leveraging the data they already collect through daily operations. It's about how they are gaining a better insight into where their efforts are best spent to maximize their return on investment or capitalize on a previously masked rich subset of their existing customer base.
If you're looking for a technical breakdown of how these algorithms work or are applied there are dozens of other books that Eric recommends as followup (referenced in probably the best notes section of any book I've ever seen).
If you want a taste of the kind of information that you'll find in the book you should look on the Predictive Analytic World website for his keynote speech he did in Boston last year. It's a great book overview and convinced me to purchase the book.
14 of 15 people found the following review helpful.
See all 298 customer reviews...
An Excellent Book by a Knowledgeable Author
By Timothy W. Daciuk
In respect of full disclosure I have known Eric for years in his capacity as founder of the Predictive Analytics World conference, and in my work in data mining and predictive analytics. That having been said, this is an excellent book for anyone who wants to learn what predictive analytics is, and how predictive analytics may be deployed across a wide range of disciplines. If you are looking for a hardcore set of algorithms or code examples this is not the book for you, and other reviewers have commented on that. I don't think that was the point of Eric's work. Eric's work does provide a review of what I think are the main pillars of predictive analytics; data, modeling, ensembles, uplift, unstructured data, deployment and ethics. If I had an issue with this book it would be in the ordering of the chapters, but, that is my personal view, and I can see why the book was structured the way that it was. The book will help you understand the major themes of predictive analytics, written in a way that let's the reader focus on the outcome, the advantages and the possibilities around predictive analytics. It is an 'easy' read yet still contains valuable insights. If you want to understand what people are talking about when they are talking about predictive analytics, read this book.