Not all machine learning models are created equal. More advanced methods lead to greater accuracy, but at the expense of interpretability. This talk will discuss how to utilize SHAP (SHapley Additive exPlanations) in R and Python to understand and interpret the results of complex machine learning models without sacrificing accuracy or interpretability.
Brianna is an experienced Data Scientist working in the consumer goods industry. She is skilled in advanced analytics, data strategies & leadership, global collaboration, and analytic consulting.
Thursday May 30, 2019 1:15pm - 2:00pm CDT
(E) P0806 A&BNormandale Partnership Center, 9700 France Ave So, Bloomington, MN 55431
