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Eric Siegel  

Founder of Predictive Analytics World, Machine Learning Expert & Acclaimed Author

The power of prediction is booming right now. Companies, governments, law enforcement, hospitals, and universities are all tapping into that power. Adam Siegel helps audiences understand how the the world’s most unnatural resource—data—is helping institutions predict whether you're going to “click, buy, lie, or die.”

On stage, this former Columbia University professor and founder of Predictive Analytics World unpacks the power and the perils of prediction. Siegel shares his expertise in machine learning and helps audiences understand how this omnipresent science affects our daily lives. Whether you are a consumer of it — or consumed by it —the power of Predictive Analytics is here to stay.

After Columbia, Siegel co-founded two software companies for customer profiling and data mining, and then started Prediction Impact in 2003, providing predictive analytics services and training to mid-tier through Fortune 100 companies. Siegel is the instructor of the acclaimed online training program, Predictive Analytics Applied. He has published over 20 papers and articles in data mining research and computer science education and has served on 10 conference program committees. He is the author of the acclaimed book, "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die."

Speech Topics

Predictive Analytics: Delivering on the Promise of Big Data

The excitement over “big data” has grown dramatically. But what is the value, the function, the purpose? The most actionable win to be gained from data is prediction. This is achieved by analytically learning from data how to render predictions for each individual. Such predictions drive more effectively the millions of operational decisions that organizations make every day. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel reveals how predictive analytics works, and the ways in which it delivers value to organizations across industry sectors

How Predictive Analytics Fortifies Healthcare

Predictive analytics addresses today’s pressing challenges in healthcare effectiveness and economics by improving operations across the spectrum of healthcare functions, including:

  • Clinical services and other healthcare management operations such as targeting screening and compliance intervention
  • Insurance pricing and management
  • Healthcare product marketing

Applied in these areas, predictive analytics serves to improve patient care, reduce cost, and bring greater efficiencies. In this keynote address, Eric Siegel will cover today’s rapidly emerging movement to fortify healthcare with big data’s biggest win: the power to predict.

Uplift Modeling: Optimize for Influence and Persuade by the Numbers

Data driven decisions are meant to maximize impact - right? Well, the only way to optimize influence is to predict it. The analytical method to do this is called uplift modeling (aka, persuasion modeling). This is a completely different animal from standard predictive models, which predict customer behavior. Instead, uplift models predict the influence on an individual’s behavior gained by choosing one treatment over another. In this session, Predictive Analytics World Founder Eric Siegel provides an introduction to this growing area.

Weird Science: How to Know Your Predictive Discovery Is Not BS

“An orange used car is least likely to be a lemon.” At least that’s what was claimed by The Seattle Times, The Huffington Post, The New York Times, NPR, and The Wall Street Journal. However, this discovery has since been debunked as inconclusive. As data gets bigger, so does a common pitfall in the application of standard stats: Testing many predictors means taking many small risks of being fooled by randomness, adding up to one big risk. John Elder calls this issue vast search. In this keynote, PAW founder Eric Siegel will cover this issue and provide guidance on tapping data’s potential without drawing false conclusions.


Sound Data Science: Avoiding the Most Pernicious Prediction Pitfall
ARTICLE: Data science and predictive analytics’ explosive popularity promises meteoric value, but a common misapplication readily backfires. The number crunching only delivers if a fundamental – yet often omitted – fail-safe is applied.

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