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Synopsis
"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 12 languages
An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) 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 (aka machine learning) 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.
"synopsis" may belong to another edition of this title.
From the Back Cover
TRANSLATED INTO 12 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, founder of the Predictive Analytics World conference series and executive editor of The Predictive Analytics Times, makes the how and why of predictive analytics (aka machine learning) understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.
Eric has appeared on Al Jazeera America, Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.
"About this title" may belong to another edition of this title.
- PublisherWiley
- Publication date2016
- ISBN 10 1119145678
- ISBN 13 9781119145677
- BindingPaperback
- LanguageEnglish
- Number of pages368
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