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Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, by Eric Siegel
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“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 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.
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Product details
Hardcover: 320 pages
Publisher: Wiley; 1 edition (February 19, 2013)
Language: English
ISBN-10: 1118356853
ISBN-13: 978-1118356852
Product Dimensions:
6.3 x 1.1 x 9.3 inches
Shipping Weight: 7.2 ounces (View shipping rates and policies)
Average Customer Review:
4.0 out of 5 stars
320 customer reviews
Amazon Best Sellers Rank:
#111,100 in Books (See Top 100 in Books)
Eric Siegel is telling it all regarding predictive analytics. He suggests people are having their behavior examined and collected by corporations, political think tanks, etc. Great read!
I'm not really sure what the purpose of this book is. As far as I can tell it's just a loosely organized list of simplistic anecdotes related to predictive analytics. Did you know that Target can predict when you're pregnant!? Did you know that a guy put his life savings into a trading bot in the 90s!? That's about all I've learned from this book. The author goes too far in his quest for accessibility and removes any interesting details that would educate someone on how these models were conceived, built, or tested. I wasn't expecting a textbook, but this is book is so far in the other direction I just can't see how reading all 300+ pages is a productive use of anyone's time. Being interested in building predictive models myself, I've been sorely disappointed.Someone who is very non-technical may appreciate the author's style, but how many non-technical people are really going pick up a book titled "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.-Greg
I do (and teach) predictive analysis for a living and love this book, not because it has technical advice that I will use, but instead because it is a *beautifully* written introduction that I can give to people who have no technical background. It is a great book for a high school senior who is thinking about going into any applied mathematical area (like economics or biostatistics). If you have expertise in other areas and if you keep hearing about topics like machine learning or artificial intelligence, IBM Watson or the Netflix Prize and if you want to get a feel for the area this is the book for you.The quotes and examples frequently tie back into financial modeling but every domain is touched. Rather than being a book on math, this is equal parts history and social science. So, this book will be enjoyable for a wide audience.
A good book if you want to get a better understanding of artificial intelligence. It's is not an how-to-do-book but it will hopefully change how you think about data.
The book addresses the many ways in which predictive analytics are being used to try to anticipate the future in business, health care, public safety, social science, etc. It’s valuable information for anyone who wants to see how AI and big data are influencing our lives. It is not a how-to guide describing the underlying mathematics, but rather a nontechnical description of the uses and effects in many areas.
This book is a great introduction to how organizations use data about you, often provided by you, to determine your behavior. It talks about the many different areas that predictive analytics are used in from advertising to health care. If you don't understand why google or facebook are free you should read this book. If you have privacy concerns about those organizations you should read this book.If you already have a decent understanding of predictive analytics this book may not be what you are looking for but it does provide information on a number of sources do delve deeper into the subject. This book deepened my knowledge of predictive analytics and pointed me to a number of sources that I am checking out to learn even more.
Good read. This is a very good overview of where modern analytics is used and what it can do. I would have enjoyed more nuts and bolts of analytics though.
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