Slides for "What Happens After the Model?" presented on March 19th at the 2024 Pharmaceutical Data Science Conference.
Abstract:
Machine learning models are everywhere now. We must spend more time on what happens before and after the model fit to build higher-quality algorithms. This talk will describe a set of post-model activities that can improve the fit and also ensure that, when deployed, it is used effectively.