", —David Leinweber, author of "Nerds on Wall Street: Math, Machines and Wired Markets", ""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. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. With this technology, the computer literally learns from data how to predict the future behavior of individuals. There was a problem loading your book clubs. ", —Jim Sterne, founder, eMetrics Summit; chairman, Digital Analytics Association. These institutions predict whether you're going to click, buy, lie, or die. Big data embodies an extraordinary wealth of experience from which to learn. Too Big to Ignore. ", — Anthony Goldbloom, Founder and CEO, Kaggle.com, "Both sophisticated and fully accessible to the non-quantitative reader. Moving beyond forecasting, true power comes in influencing the future rather than speculating on it—the raison d'être of predictive analytics. In the meantime, the Obama campaign was using predictive analytics to render per-voter predictions. Siegel goes behind the hype and makes the science exciting. Each model alone may be fairly primitive such as a few simple rules, so it gets prediction wrong a lot, as an individual person trying to predict also does. Read this book to gain understanding of where we are and where we're headed. Top subscription boxes – right to your door. It talks about the many different areas that predictive analytics are used in from advertising to health care. Takes various cases and various industry domains to explain what and how predictive analytics is used. ", —Geoffrey Moore, author of "Crossing the Chasm", "The most readable (for we laymen) 'big data' book I've come across. 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. by P. Simon. By far. Predictive Analytics unleashes the power of data. An introduction for everyone. This book is a great introduction to how organizations use data about you, often provided by you, to determine your behavior. It was a bit heavy at first, thick with facts that I found irritating and contradictory to certain favorite and closely held biases of mine, but over time, I could see his points better and better, in spite of myself. Read more. Your recently viewed items and featured recommendations, Select the department you want to search in, + $12.29 Shipping & Import Fees Deposit to Lithuania. Our payment security system encrypts your information during transmission. ", —Stephen Baker, author of "The Numerati and Final Jeopardy: The Story of Watson, the Computer That Will Transform Our World", "Simultaneously entertaining, informative, and nuanced. 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. ", "This book is an operating manual for 21st century life. This in turn only amplifies the stakes of the contentious security-versus-privacy debate. If you want to understand what people are talking about when they are talking about predictive analytics, read this book. Anybody interested in learning what predictive analytics is this is the book to go. ", Launch Newsletter Modal Window, Click Here. We work hard to protect your security and privacy. Siegel provides new case studies and the latest state-of-the-art techniques. Please try again. It's a foregone conclusion that the world's largest spy organization employing the world's largest number of Ph.D. mathematicians considers predictive analytics a strategic priority. What type of mortgage risk Chase Bank predicted before the recession. The NSA needs data about everyone, including those of us with no connection to crime whatsoever—not to spy on us but to establish a quantitative baseline. ", —Tom Peters, co-author of "In Search of Excellence", "An operating manual for twenty-first-century life. Why? Predictive analytics seeks out such predictive connections and then works to see how they may combine together for more precise prediction. To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. ", —Rayid Ghani, Chief Data Scientist, Obama for America 2012 Campaign, ""Moneyball" for business, government, and healthcare. Unable to add item to List. University of Zurich discovered that, for a certain working category of males in Austria, each additional year of early retirement decreases life expectancy by 1.8 months. Drawing predictions from big data is at the heart of nearly everything, whether it's in science, business, finance, sports, or politics. This book is extremely introductory, which accounts for Siegel's 50,000-foot view of the topic. A truly omnipresent science, predictive analytics constantly affects our daily lives. - Netflix sponsored a $1 million competition to predict which movies you will like in order to improve movie recommendations. Like the collective intelligence that spawns the wisdom of a crowd of people, we see the same effect with a crowd of predictive models. © 1996-2020, Amazon.com, Inc. or its affiliates. A broad, well-written book easily accessible to non-nerd readers. Surprise! In fact, I liked it so much I have assigned it as a required reading for an MBA class I’m teaching. A great narrative into the field of Predictive Analytics, not much maths, perhaps for the first foray into this field. Takes various cases and various industry domains to explain what and how predictive analytics is used. We don’t share your credit card details with third-party sellers, and we don’t sell your information to others. This shopping feature will continue to load items when the Enter key is pressed. 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: How does predictive analytics work? Another hot trend is ensemble models. "persuasion modeling"), which predicts influence. It is an 'easy' read yet still contains valuable insights. Also, explains what machine learning is in simple terms to a novice. 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. 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. One is "uplift modeling" (a.k.a. Please try your request again later. The book gives a very good introduction on for predictive analytics. With a foreword from Thomas H. Davenport, coauthor of Competing on Analytics. The value of this capability multiplies the incentive to collect increasing amounts of data about civilians.

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