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Predictive Analytics
- The Power to Predict Who Will Click, Buy, Lie, or Die, Revised and Updated
- ナレーター: Steven Menasche
- 再生時間: 11 時間 6 分
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あらすじ・解説
"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer
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 listeners 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, Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction:
- What type of mortgage risk Chase Bank predicted before the recession.
- Why vegetarians miss fewer flights.
- How US 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 companies ascertain untold, private truths - how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job.
- 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.
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.