By: Eric Siegel, Founder, Predictive Analytics World
Originally published by Scientific American
Data is the world’s most potent, flourishing unnatural resource. Accumulated in large part as the by-product of routine tasks, it is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is inherently predictive. Thus begins a gold rush to dig up insightful gems. Does crime increase after
By: Eric Siegel, Founder, Predictive Analytics World
Originally published in Analytics Magazine
This article is excerpted from Eric Siegel’s foreword to the recently released book, Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics, by Jeff Deal and Gerhard Pilcher....
In anticipation of his upcoming conference keynote presentation, 21st Century Data-Driven Environmental Protection at Predictive Analytics World for Government, October 17-20, 2016, we asked Robin Thottungal, Chief Data Scientist/Director of Analytics at the U.S. Environmental Protection Agency...
By: Eric Siegel, Founder, Predictive Analytics World
Originally published in Scientific American and Salon
In this article, I provide evidence that Hillary for America is employing uplift modeling for per-voter persuasion—which Trump’s campaign may not be taking advantage of—and I pose questions about the 2016 presidential race to a leading...
In anticipation of his upcoming conference co-presentation, Words that Matter: Application of Text Analytics at the U.S. Commodity Futures Trading Commission, at Predictive Analytics World for Government, October 17-20, 2016, we asked Miguel Castillo, Assistant Inspector General...
In anticipation of his upcoming keynote co-presentation, Picking the Right Modeling Technique for the Problem, at Predictive Analytics World London, October 12-13, 2016, we asked Michael Berry, Analytics Director at TripAdvisor Hotel Solutions, a few questions about...
By: Richard Boire, Senior Vice President, Environics Analytics
Continuing on our discussion from last month on toolkits for practitioners, you will note that I purposely do not make reference to specific brand names and companies. By googling data science software, the user can easily obtain...
By: Ryan McGibony, Data Scientist, Elder Research
Research shows that people tend to be overly risk averse when weighing the potential success or failure of a decision. This tendency is compounded when we consider the vast number of decisions being made across an organization....
By: Bala Deshpande, Founding Partner, SimaFore & Chair, PAW – Manufacturing
Predictive analytics is increasingly becoming the object of value within many so-called traditional industries like manufacturing. While historically data generated by and in manufacturing is mostly structured, today unstructured data is also becoming a source that cannot...
By: Eric Siegel, Founder, Predictive Analytics World
Here are six key definitions—and The Five Effects of Prediction—from my book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (Revised and Updated, 2016). Note: A complementary copy of this book will...
 |
 |
 |
The Machine Learning Times © 2020 • 1221 State Street • Suite 12, 91940 •
Santa Barbara, CA 93190
Produced by: Rising Media & Prediction Impact