Contributor: Shannon Kelley
Role: Graduate student
Affiliation: College of Engineering, Industrial and Systems Engineering
Abstract: This project outlines the most common sources of errors users face with data science models, which includes when a model returns wrong outputs, varies output by release, crashes, misses the latest features, and doesn’t run in a new environment. Solutions to these issues are demonstrated with coding examples.