Abstract: 

One of the holy grails of machine learning is orchestrating a continuous learning platform in real-time – one that adapts as the population changes. Because the fact is, models begin to degrade as soon as they are deployed. And model fairness and bias must always be addressed.

That’s why it’s so important to monitor model drift, retrain champion models and evaluate new challengers. The most advanced organizations do this by running model training services at the edge. We will discuss how you can do the same to ensure you get the most value out of machine learning efforts.

Bio: 

Wayne Thompson, Chief Data Scientist at SAS, is a globally renowned presenter, teacher, practitioner and innovator in the fields of data mining and machine learning. He has worked alongside the world's biggest and most challenging organizations to help them harness analytics to build high performing organizations. Over the course of his 24 year tenure at SAS, Wayne has been credited with bringing to market landmark SAS analytics technologies, including SAS Text Miner, SAS Credit Scoring for Enterprise Miner, SAS Model Manager, SAS Rapid Predictive Modeler, SAS Visual Statistics and more. His current focus initiatives include easy to use self-service data mining tools along with deep learning and cognitive computing tool kits.