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Predictive Analytics : the Power To Predict Who Will Click, Buy, Lie, Or Die /
"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, fasci...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley,
2016.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Siegel, Eric. | |
| 245 | 1 | 0 | |a Predictive Analytics : |b the Power To Predict Who Will Click, Buy, Lie, Or Die / |c Eric Siegel. |
| 260 | |a Hoboken, N.J. : |b Wiley, |c 2016. | ||
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| 520 | |a "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-and Hillary for America 2016 plans to calculate-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.-183 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 dus 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. | ||
| 500 | |a Title from resource description page (Recorded Books, viewed March 28, 2016). | ||
| 505 | 0 | |a Praise for Predictive Analytics; Title Page; Copyright; Dedication; Foreword Thomas H. Davenport; Preface to the Revised and Updated Edition; Frequently Asked Questions about Predictive Analytics; Preface to the Original Edition; Introduction: The Prediction Effect; Prediction in Big Business-The Destiny of Assets; Introducing ... the Clairvoyant Computer; "Feed Me!"-Food for Thought for the Machine; I Knew You Were Going to Do That; The Limits and Potential of Prediction; The Field of Dreams; Organizational Learning; The New Super Geek: Data Scientists; The Art of Learning. | |
| 505 | 8 | |a Chapter 1: Liftoff! Prediction Takes ActionGoing Live; A Faulty Oracle Everyone Loves; Predictive Protection; A Silent Revolution Worth a Million; The Perils of Personalization; Deployment's Detours and Delays; In Flight; Elementary, My Dear: The Power of Observation; To Act Is to Decide; A Perilous Launch; Houston, We Have a Problem; The Little Model That Could; Houston, We Have Liftoff; A Passionate Scientist; Launching Prediction into Inner Space; Chapter 2: With Power Comes Responsibility: Hewlett-Packard, Target, the Cops, and the NSA Deduce Your Secrets. | |
| 505 | 8 | |a The Prediction of Target and the Target of PredictionA Pregnant Pause; My 15 Minutes; Thrust into the Limelight; You Can't Imprison Something That Can Teleport; Law and Order: Policies and Policing of Data; The Battle over Data; Data Mining Does Not Drill Down; HP Learns about Itself; Insight or Intrusion?; Flight Risk: I Quit!; Insights: The Factors behind Quitting; Delivering Dynamite; The Value Gained from Flight Risk; Predicting Crime to Stop It Before It Happens; The Data of Crime and the Crime of Data; Machine Risk without Measure; The Cyclicity of Prejudice. | |
| 505 | 8 | |a Good Prediction, Bad PredictionThe Source of Power; Chapter 3: The Data Effect: A Glut at the End of the Rainbow; A Cautionary Tale: Orange Lemons; The Source: Otherwise Boring Logs Fuel Prediction; Social Media and Mass Public Mood; Recycling the Data Dump; The Instrumentation of Everything We Do; Batten Down the Hatches: TMI; Who's Your Data?; The Data Effect: It's Predictive; The Building Blocks: Predictors; Far Out, Bizarre, and Surprising Insights; Caveat #1: Correlation Does Not Imply Causation; Caveat #2: Securing Sound Discoveries; What Went Wrong: Accumulating Risk. | |
| 505 | 8 | |a The Potential and Danger of Automating Science: Vast SearchA Failsafe for Sound Results; A Prevalent Mistake; Putting All the Predictors Together; Chapter 4: The Machine That Learns: A Look inside Chase's Prediction of Mortgage Risk; Boy Meets Bank; Bank Faces Risk; Prediction Battles Risk; Risky Business; The Learning Machine; Building the Learning Machine; Learning from Bad Experiences; How Machine Learning Works; Decision Trees Grow on You; Computer, Program Thyself; Learn Baby Learn; Bigger Is Better; Overlearning: Assuming Too Much; The Conundrum of Induction. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
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| 776 | 0 | 8 | |i Print version: |a Siegel, Eric. |t Predictive Analytics : The Power to Predict Who Will Click, Buy, Lie, or Die. |d : Wiley, ©2016 |z 9781119172536 |
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