How the COVID-19 Pandemic is Accelerating the Need for Model Monitoring | Transforming Data with Intelligence
Once in production, a model's behavior can change if production data diverges from the data used to train it. In other words, the behavior of a model is determined by the picture of the world as it was during training. When real-world data diverges from the picture "learned" by the model -- a phenomenon known as drift -- models perform poorly or, in the worst cases, fail completely. Model Drift Has Real-World Consequences Model drift can result in severe consequences for everyone involved if it's not observed, caught, and remediated quickly. Think critical supply shortages resulting from in...
Source: tdwi.org