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Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die Hardcover – February 19, 2013

4.1 out of 5 stars 295 customer reviews

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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
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (295 customer reviews)
  • Amazon Best Sellers Rank: #136,627 in Books (See Top 100 in Books)

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By Sujit Pal on March 1, 2013
Format: Hardcover Verified Purchase
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.
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Format: Hardcover
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.
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Format: Hardcover Verified Purchase
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!
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Format: Hardcover Verified Purchase
In respect of full disclosure I have known Eric for years in his capacity as founder of the Predictive Analytics World conference, and in my work in data mining and predictive analytics. That having been said, this is an excellent book for anyone who wants to learn what predictive analytics is, and how predictive analytics may be deployed across a wide range of disciplines. If you are looking for a hardcore set of algorithms or code examples this is not the book for you, and other reviewers have commented on that. I don't think that was the point of Eric's work. Eric's work does provide a review of what I think are the main pillars of predictive analytics; data, modeling, ensembles, uplift, unstructured data, deployment and ethics. If I had an issue with this book it would be in the ordering of the chapters, but, that is my personal view, and I can see why the book was structured the way that it was. The book will help you understand the major themes of predictive analytics, written in a way that let's the reader focus on the outcome, the advantages and the possibilities around predictive analytics. It is an 'easy' read yet still contains valuable insights. If you want to understand what people are talking about when they are talking about predictive analytics, read this book.
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Format: Kindle Edition Verified Purchase
This is a great book on the Topic. What are you going to learn. Predictive analytics, which represents a data mining or statistical solution derived from techniques and algorithms that can be used with unstructured or structured data to arrive at outcomes, has been in use for some time. Indeed, the discipline has been in use with structured data for several decades. However, the visibility and subsequent market adoption of the discipline have increased significantly in recent years as computer power has increased. Processing memory and speed have increased at exponential rates, and this novel fact has been reported on by the media. For example, TIME magazine reported that the typical smartphone in 2012 had greater computing power than all the computers it took to send Apollo 11 to the moon in 1969. Furthermore, the cost of computing power has decreased as quickly as the speed and memory capabilities have increased. This revolution in computing capability has put predictive analytics in reach of mainstream business, as a predictive model can produce outcomes in minutes rather than days. In the past, businesses could not afford the computing power necessary to gather and interpret data that changed continuously in real time. This lack of cost effective options presented obstacles to integrating the output of a predictive model into the business process. Now, with the price per CPU decreasing and the computer power increasing, predictive analytics has become a practical, even necessary tool, for most organizations. Hope this helps, overall a great book, Eric Siegel great book we should talk sometime..:)
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