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MACHINE LEARNING & AI FOUNDATIONS: A GUIDE TO PREDICTIVE MODELING

April 30, 2019 | (1:00 PM)
USA (United States of America)
Organizations are faced with increasing volumes of data, but exactly how much of that data do we need to use in our predictive analytics models, and at what point should we be worried that we might have to upgrade our modeling infrastructure? Summary Organizations are faced with increasing volumes of data, but exactly how much of that data do we need to use in our predictive analytics models, and at what point should we be worried that we might have to upgrade our modeling infrastructure? In this session, we will walk through the modeling process from start to finish and discuss how the amount of data fluctuates, often dramatically, at different stages of the project. We will review each stage—data selection, data preparation, modeling, scoring, and deployment—with scalability in mind, providing IT professionals, data scientists, and leadership with new insights, perspectives, and collaboration tools.