data drift

In the ever-evolving realm of machine learning, models are trained on historical data to make predictions about future events. However, the world is dynamic, and data distributions can change over time, leading to a decline in model performance. This phenomenon, often called “drift,” can manifest in two primary forms: data drift and concept drift. Understanding …

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