What is the purpose of Amazon SageMaker Model Monitor?

Amazon SageMaker Model Monitor is specifically designed to track the performance of machine learning models once they are deployed in a production environment. Its primary purpose is to detect data drift and performance degradation, ensuring that the models operate as intended over time and maintain their predictive accuracy. By continuously monitoring the input data and the predictions made by the model, it can identify when the model's performance declines, which might indicate issues such as changes in the data distribution that were not accounted for during the training phase.

The capability to evaluate existing models for quality issues is crucial because machine learning models can become less effective as new data emerges or as underlying patterns in the data change. This component of Amazon SageMaker helps practitioners maintain model performance, enabling prompt action to either retrain the model or adjust it in response to these detected discrepancies.