ML Drift: Your Production Model Went Stale Three Months Ago and Nobody Noticed
Machine learning models in production can become stale over time, a phenomenon known as ML drift, which can go unnoticed for months. This article suggests methods to prevent such drift by implementing end-to-end monitoring in near-real-world product examples. The focus is on ensuring the continued relevance and accuracy of deployed models. AI
