SAS | The Power to Know

Proven Practices for Predictive Modeling Webinar (hosted by SMUG)

Thursday,  June 16   |  1 – 2 p.m. ET

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This complimentary webinar is hosted by the SAS® Manufacturing Users Group.

Do you have predictive modeling projects that could benefit from additional analytical strategies? Or perhaps you’d like to increase the value and importance of analytics in your organization? At SAS, we can help.

Join our journey for analytics excellence as we share some of the common strategies, attributes, processes and best practices of the most successful organizations. Best practices will include considerations for an overall analytics process and the discrete steps of building a predictive model, such as: data preparation and sampling; input (variable) examination, selection and transformation; and model selection and validation.

About the Presenter

Portrait of Mary-Elizabeth Eddlestone

Mary-Elizabeth Eddlestone, Principal Systems Engineer, SAS Customer Loyalty

Demystifying analytics has been a career-long quest for Mary-Elizabeth (“M-E”) Eddlestone, an analytics specialist on the SAS Customer Loyalty team. Having studied economics and quantitative methods at Mount Holyoke College and Cornell University, she has used SAS Analytics to study, model, forecast and predict a wide range of subjects in a variety of industries. Eddlestone began programming in SAS as an undergraduate and has used SAS in every job since. She has spent the last several years at SAS helping customers discover the power of SAS Analytics and has presented at – and served as section chair for – SUGI/SAS Global Forum, Analytics and several regional, local and in-house SAS users groups. She has the Predictive Modeler Using SAS® Enterprise Miner™ certification.

About SMUG
The SAS Manufacturing Users Group is open to all SAS users in the manufacturing industry. Its purpose is to provide a forum for members to research and educate themselves on innovative methods and techniques and exchange ideas, information and best practices about SAS solutions.

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