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Predictive Analytics 9781119145677 Eric Siegel
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40sinds 4 sep. '24, 16:07
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AuteurEric Siegel
ConditieGelezen
Productnummer (ISBN)9781119145677
Jaar (oorspr.)2015
Beschrijving
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Titel: Predictive Analytics
Auteur: Eric Siegel
ISBN: 9781119145677
Conditie: Beetje gebruikt
"Mesmerizing & fascinating. " The Seattle Post-Intelligencer "The Freakonomics of big data. " Stein Kretsinger, founding executive of Advertising.
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
"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 (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:
BoekenBalie maakt van tweedehands jouw eerste keuze. Met een Trustscore van 4,8 (excellent) en 30 dagen retour garantie maken we dat iedere dag waar.
Titel: Predictive Analytics
Auteur: Eric Siegel
ISBN: 9781119145677
Conditie: Beetje gebruikt
"Mesmerizing & fascinating. " The Seattle Post-Intelligencer "The Freakonomics of big data. " Stein Kretsinger, founding executive of Advertising.
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
"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 (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.
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