Estimating Model Performance without Ground Truth

It’s possible, as long as you keep your probabilities calibrated

It should be no news to data science folks that once a predictive model is finally deployed, the fun is only starting. A model in production is like a baby: it needs to be observed and babysat to ensure it’s doing alright and nothing too dangerous is going around. One of the babysitter’s main chores is to constantly monitor the model’s performance and react if it deteriorates. It is a …

artificial intelligence data science machine learning mlops performance programming