Too Long; Didn't Read
Machine Learning (ML) life cycle involves six key stages: data collection, data processing, data labeling, model training/evaluation, model deployment, and model monitoring. The last stage of the chain (i.e., model monitoring) was one of the least liked and most dreaded stages of the whole life cycle. Many ML engineers working on AI products are often forced to “face the music” in the final stages. The big question is how do you know if your model is doing a good job when new user data starts pouring in?