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Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (Englisch) Gebundene Ausgabe – 8. März 2013

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  • Gebundene Ausgabe: 320 Seiten
  • Verlag: John Wiley & Sons; Auflage: 1. Auflage (8. März 2013)
  • Sprache: Englisch
  • ISBN-10: 1118356853
  • ISBN-13: 978-1118356852
  • Größe und/oder Gewicht: 16 x 2,8 x 23,6 cm
  • Durchschnittliche Kundenbewertung: 3.5 von 5 Sternen  Alle Rezensionen anzeigen (2 Kundenrezensionen)
  • Amazon Bestseller-Rang: Nr. 30.578 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
  • Komplettes Inhaltsverzeichnis ansehen

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Praise for Predictive Analytics
"What Nate Silver did for poker and politics, this does for everything else. A broad, well-written book easily accessible to non-nerd readers."
--DAVID LEINWEBER, author of Nerds on Wall Street: Math, Machines and Wired Markets
"This book is an operating manual for twenty-first-century life. Drawing predictions from big data is at the heart of nearly everything, whether it's in science, business, finance, sports, or politics. And Eric Siegel is the ideal guide."
--STEPHEN BAKER, author of The Numerati and Final Jeopardy: Man vs. Machine and the Quest to Know Everything
"Simultaneously entertaining, informative, and nuanced. Siegel goes behind the hype and makes the science exciting."
--RAYID GHANI, Chief Data Scientist, Obama for America 2012 Campaign
"This is Moneyball for business, government, and healthcare."
--JIM STERNE, founder, eMetrics Summit; chairman, Digital Analytics Association
"Predictive Analytics is not only a deeply informative dive into a topic that is critical to virtually every sector of business today, it is also a delight to read."
--GEOFFREY MOORE, author of Crossing the Chasm
"The future is right now--you're living in it. Read this book to gain understanding of where we are and where we're headed."
--ROGER CRAIG, record-breaking analytical Jeopardy! champion; CEO, Cotinga


You have been predicted-by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die.
Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.
How? Prediction is powered by the world's most potent, booming 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-lifting a bit of the fog off our hazy view of tomorrow-means pay dirt.
In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction:
* What type of mortgage behavior Chase Bank predicted
* Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves
* Why early retirement decreases life expectancy and vegetarians miss fewer flights
* Five reasons why organizations predict death
* How U.S. Bank and Obama's 2012 campaign calculated the way to most strongly influence each individual
* How IBM's Watson computer beat the human champs on TV's Jeopardy!
* 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 who stays in prison and who goes free
* What's predicted by Citibank, Facebook, Ford, Google, IBM, the IRS,, Pfizer, and Wikipedia
A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. Whether you are a consumer of it-or consumed by it-get a handle on the power of Predictive Analytics.

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Die hilfreichsten Kundenrezensionen

Format: Kindle Edition Verifizierter Kauf
A book by Eric Siegel that gives an introduction to Predictive Analytics and contains principles, ethics, terminology, industry-specific applications, stories and additional resources of Predictive Analytics. Eric Siegel is in the field of Predictive Analytics (and Data Mining) for at least a decade now, and carries attributes of a thought leader in his field. The cross-section stories give the book content a concrete tendency and make it accessible and relatable for virtually every reader. The numerous resources make it a start point for the Predictive Analytics fresher with higher ambitions. Start here if you are interested in Predictive Analytics!
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0 von 1 Kunden fanden die folgende Rezension hilfreich Von snowvirus am 20. September 2014
Format: Kindle Edition Verifizierter Kauf
Very hot topic. Siegel gives impressive and pertinent examples to make his point on predictive anayitics. Unfortunatly, he wastes countless pages rambling on distant personal memories.
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Die hilfreichsten Kundenrezensionen auf (beta) 238 Rezensionen
47 von 55 Kunden fanden die folgende Rezension hilfreich
Online Data Converts to a Plethora of Predictions 18. Februar 2013
Von connywithay - Veröffentlicht auf
Format: Gebundene Ausgabe
Title: Predictive Analytics - The Power to Predict Who Will Click, Buy, Lie or Die
Author: Eric Siegel
Publisher: John Wiley & Sons, Inc.
ISBN: 978-1-118-35685-2

With the astronomical mass of electronic data collected today, one may be wary of driving a GPS-tracked automobile, texting on a cellphone, purchasing grocery items with a credit card, posting on Facebook, anxiously blogging or clicking a mouse for information on Google. But to Eric Siegel, this collective and easily-available data is fascinating as he compiles, analyzes and predicts in his eye-opening book, "Predictive Analytics - The Power to Predict Who Will Click, Buy, Lie or Die."

In a little over three hundred pages in the hardbound book, Siegel breaks down predictive analytics (aka PA) into seven chapters with an afterword, appendices, notes, acknowledgement, author biography and index. The book is targeted from the small to large business owner, entrepreneurs, other PAers and us common folk who want to further understand how computerized data research is analyzed to predict specified outcomes and scenarios.

Cause and effect charts, illustrations along with a few comics and a glossy centerfold divulge cases of predictions in advertising, finance, healthcare, fraud, insurance, government, employment and personal venues. Some topics discussed explain ways to increase consumer buying, limit bank loan defaulting or paying off, anticipate employees quitting or clients dropping cellphone coverage along with collecting online blogs, social networking and risk information. Each chapter includes sections of "what's predicted" and "what's done about it" to show the correlation of PA and gathered data.

The author explains the art of predicting has five effects that include: a little prediction goes a long way, data is always predictive, induction is reasoning from detailed facts to general principles, ensembles compensate for limitations and persuasion can be predictable through outcomes. Using the predictive models of large corporations such as Target, Hewlett-Packard, Chase Bank, Netflix and Telenor along with John Elder's stock market techniques, Jeopardy!'s Watson computer, Kaggle's competitions, and Obama's second term presidential campaign, one learns the ins and outs of predicting through collecting and interpreting simple to complex data.

By entrusting computers to make decisions, privacy concerns are bought up, prejudices are determined and effects are manipulated when machine learning becomes the translated voice of data. Artificial intelligence can often limit overlearning, crowdsourcing and correlation pitfalls, but will it be able to always correctly interpret language, emotions and feelings of humans as it influences, persuades and molds us?

With even the book's title been subjected to analysis and written sometimes humorously of the writer's own experience of stolen identity and mockery of his geekness, it is an excellent source to any reader that sees computers overtaking and controlling our every move as we continue to be co-dependent on them as we happily benefit from increased information and understanding, attain higher profits and enjoy an easier lifestyle through such a conglomerate of PA data bytes. The only remaining question is how much PA will be gleaned from this book reviewer's post?
34 von 39 Kunden fanden die folgende Rezension hilfreich
Bringing Predictive Analytics to the masses 2. März 2013
Von Sujit Pal - Veröffentlicht auf
Format: Gebundene Ausgabe Verifizierter Kauf
This book is aimed mostly at people who are interested in learning about where (as opposed to how) one can effectively use Predictive Analytics and related technologies such as Machine Learning and Natural Language Processing. There is some high level discussion of algorithms such as linear regression, decision trees, random forests and even a nice discussion about Watson's question answering algorithms. The book has many examples of where Predictive Analytics can and is being used. Some of these are relatively obscure, because companies prefer to make money off these techniques rather than talk about it (and dilute their competitive edge). The narrative is interesting and humorous, and the author shares many anecdotes from his own life, having lived through Predictive Analytics relatively short life-span. Finally, the bibliography/reference section lists URLs that will probably take you months to get through. All in all, a "popular" book aimed at people who are looking into learning about and/or adopting Predictive Analytics rather than established practitioners, but very useful and well written nevertheless.
29 von 36 Kunden fanden die folgende Rezension hilfreich
Good Stuff! 27. Februar 2013
Von jasonhoward7 - Veröffentlicht auf
Format: Gebundene Ausgabe Verifizierter Kauf
I'm an IT guy. When I read and research I want solid concepts and clear explanations. This book has it all without missing a step. Even better, Siegel delivers his insight with humor and inventiveness. This book is jammed packed with real world applications for Predictive Analytics, told with a colorful, dramatic flair. Read it! Good Stuff!
12 von 15 Kunden fanden die folgende Rezension hilfreich
Predict This 21. Februar 2013
Von Amazon Customer - Veröffentlicht auf
Format: Gebundene Ausgabe Verifizierter Kauf
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die is a book for anyone in any field of work. It puts into layman's terms how you can apply analytics to your business, whether that be human resources, insurance, direct sales, medical field, even teachers. I'm being predicted every day and now I know how! Thanks to Eric Siegel for writing a book on this subject that anyone can understand and its funny!
16 von 21 Kunden fanden die folgende Rezension hilfreich
Serious, unnecessary mistake 26. April 2013
Von Beau Sabreur - Veröffentlicht auf
Format: Gebundene Ausgabe
This book is a lighthearted survey of predictive analytics and what you can do with it; essentially a tour d'horizon. A section is devoted to the very important issue of ethics and responsibility in the use of analytics, and that is good. However, the author makes a very serious mistake that compromises the seriousness of the book and misleads readers about the understanding of the power and limitations of analytics. He tells us about a John Elder who seems to have created a black box to trade in stocks, having invested all his family money in the project including his retirement fund. This, I find an egregious example of irresponsibility, but that is another story.

It seems that Mr Elder was successful in his "all or nothing bet" and that he attracted millions in investors' money. As the story goes, Mr. Elder invested the funds using his black box during nine years.....but then, the author informs us that "all good things must come to an end...." and that "he was running on fumes" (What kind of professional talk is that?) and the fund was disbanded..but that "everyone came out ahead..." By how much? Was it by 50%, 20%, 5%, 0.0000001%?

I risk say that during the 9 years, Mr Elder made some money and lost some -like most fund managers, until his investors and probably he too became disillusioned with the results and decided to pull the plug.

This bothers me, and it bothers me a lot. First of all, the stock exchange is a complex system (as in Complexity Theory) and it is not possible to use analytics to consistently make money, obtaining results the way you can with other areas mentioned in the book, which are NOT complex systems.

The author goes on to tell us about two students who carried out a study to predict stock prices based on emotions. Predictably (no pun intended) the study came to nothing meaningful. On page #73 he also refers to the S&P 500 oscillations as chaotic.... Is he using the word "chaotic" in colloquial parlance? I say this because the stock market is NOT chaotic (as in Theory of Chaos).

It would seem that the author is not familiar with Complexity Theory, but that is OK. What is NOT OK is that he is including a complex system in a book which supposedly educates you about analytics!. Even if he is totally ignorant about Complexity Theory, he should by his own experience -which I assume he has- know that the stock market is not a good example of the benefits of using predictive models based on analytics. It is actually, the wrong, misleading example.

Is analytics as well as predictive models used to manage money? Absolutely yes. But results have hardly been consistent. No one has until now been able to create successful predictive models involving analytics to consistently make money in the stock market. Do people try? They do it all the time, the same way as "economists" make predictions about the economy (another complex system). Do I need to remind you all the disastrous "predictions" these "experts" constantly inflict upon us? Do I need to remind you that notwithstanding this, they continue hard at it?

Does it mean analytics will never be able to generate consistent results related to complex systems? No. I think this may be possible in the future, but the technology is not available right now.

The author should in a next edition, completely excise the "Stock exchange story" from the book.
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