A Perfect Machine Learning Training Data Set?
“What is good enough” is a living question that has evolved over the span of the ramp project. It starts at the end, in defining our use case and engaging end-users as advisors to get an idea of how the model outputs will be utilized. Working backward in this way has allowed us to craft our approach to establishing training data guidance and quality assurance . . .