Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
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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 (aka machine learning) 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(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 — 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 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.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.
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.
ASIN : 1119145678
Publisher : Wiley; Revised and Updated edition (January 20, 2016)
Language : English
Paperback : 368 pages
ISBN-10 : 9781119145677
ISBN-13 : 978-1119145677
Item Weight : 2.31 pounds
Dimensions : 6 x 1.3 x 8.9 inches
Customers say
Customers find the book provides a good overview of the topic and solid layman’s definitions. They say it’s a great introduction to an extraordinary discipline and valuable information for anyone who wants to see how AI and big data are influencing. Readers describe the book as well-written, readable, and worth reading. They also mention the concepts are clearly explained and humorously presented.
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11 reviews for Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
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Stewart Paulson –
Predictive Analytics
Eric Siegel describes the historical use and proven value of predictive analytics and describes the how, why and when predictive analytics, has been used as an effective tool for improving decision making in social institutions as well as retail, and commercial/industrial business. One of the great strengths of this book is that Eric Siegel provides a wealth of links to web sites where one can find additional information on predictive analytics, written by the leaders/experts in this field . An objective, well researched and well written book . Predictive analytics is described as a tool that provides management with more information for intelligent and accountable decision making. Predictive analytics has been proven in sports and elections as well as in insurance, finance, marketing and medicine as having huge potential for assisting management in making better decisions, particularly with respect to strategy and resource allocation. Siegel describes how social networking is being used to enhance decision making in marketing and providing management with a better understanding of the needs and preferences of their customers. He also discusses the difficulties that have been faced by the proponents of predictive analytics and how he and other proponents have dealt with critics, such as media that have express concern over privacy issues. Predictive analytics, like many advancements have faced regulatory changes and call for disciplined moral responsibility in their application, particularly where social communication is being integrated with other data bases for decision making by corporate and social/political leaders. With this sidebar Siegel goes on to focus on the tremendous benefits of predictive analytics and the numerous areas it is being used in with great success. This book is a six star book in a 5 star world.
Kindle Customer –
solid intro to the uses of PA
I read this book as it was required by a graduate level course about predictive analytics. Overall I enjoyed this book, Siegel has an engaging writing style and a very passionate stance on the value of PA. As an intro to the field it is great, full of real world examples. Siegel is a great storyteller and for the most part did not learn my interest. My only quibble is not enough detail on the nuts and bolts of how these predictive models really work, which I constantly found myself wanting more detail on. But I understand this is an intro to the field and it’s uses, not a how-to manual. Worth reading if you have any interest in predictive analytics or the uses of modeling technology to drive decision making.
RusticTraveller –
Eric Siegel Great Book
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..:)
URmem –
Just OK
It’s a brief introduction to some predictive analytics and a lot of examples more or less relevant. However, it does not go deep neither in the predictive analytics techniques neither in the examples so, overall, it is a very superficial book. It is interesting for around 20% of the book but then it does not provide new concepts after that. 40% of the book (!) is just references with numerous links that are irrelevant and part of the research that the author should keep to himself since, first, most links are outdated or there is no need to consult them. I learn some things and three stars is a generous rating.
I Teach Typing –
Beautiful non-technical writing
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.
Long-time Amazon Customer –
Provides clarity in a world of confusion
I purchased Eric’s book not sure of what to expect. Would he provide an overly technical look at the world of predictive analytics or a dumbed down overview of a very complex subject? I was pleasantly surprised that the book strikes a great balance of providing information in a way that’s clear and understandable without being overly simplistic. If you want to understand how data is transforming the world (and what it means for our everyday lives), this is a great primer.
Gustavo –
IncrÃvel, uma visão abrangente de aplicações de métodos preditivos! Recomendo!
Stew7sx –
Questo libro è un must have per chi vuole approcciarsi alla Predictive Analysis. Non è astruso ne complesso da capire. Ottimo incipit per chi è alle prime armi ed è interessato a capire inanzitutto le applicazioni pratiche.
Ruben Sanpal –
The book has the information applied to reality
Christian Gallardo –
Un buen libro para comenzar. Regulares ejemplos.
Fernando –
Análisis predictivo es descrito por el autor como la tecnologÃa que aprende de los datos para predecir el comportamiento futuro de los individuos con el propósito de tomar mejores decisiones. El libro nos ingresa a las raÃces de este tema para entender su funcionamiento. El libro está dirigido al público en general y esto lo menciona el mismo autor catalogando el libro como âtotalmente conceptualâ incluyendo casos de la vida real como ejemplos del uso del análisis predictivo. Debido a esto, el lenguaje literario que utiliza el autor es un lenguaje común, no estilizado y sin intención estética para un mejor entendimiento de cada uno de los conceptos.El argumento del libro es el poder explicar de forma simple y a cualquier persona, qué es el análisis predictivo, técnica que ha sido adoptada cada vez más por las empresas duplicándose en los últimos años, y la cual menciona se ha utilizado en toda industria destacando el comercio, manufactura, salud gobierno y leyes. El argumento del autor se basa en el supuesto de que el análisis predictivo ha sido, en lo general, bueno para la humanidad, pero dejando muy claro el hecho de que esta tecnologÃa puede ser usada tanto para bien como para mal. Eric clasifica BI y Analytics como prioridad número uno de inversión para los CIOs y explica las razones en el libro.El autor ha colaborado en varios proyectos de implementación de PA en varias organizaciones y ha podido ver el poder que esta tecnologÃa tiene, por esta razón, la opinión del autor siempre se basa en que es una técnica revolucionaria para todas las industrias. Un gran libro para comenzar a entrar en el mundo de PA de una forma teórica y con grandes casos de éxito como ejemplos que fundamentan dicha teorÃa.