Day 52: Concept Drift: Detecting Changes in Feature-Target Relationships
Welcome back, architects of tomorrow's AI. In our last session, we dissected Covariate Shift, understanding how changes in input data distribution (P(X)) can silently erode model performance. Today, we confront an even more insidious adversary: Concept Drift. This isn't just about your data looking different; it's about the very essence of what your model learned becoming obsolete.