In the context of model deployment, _______ is the process of ensuring the model's predictions remain consistent and accurate over time.

  • Monitoring
  • Training
  • ETL
  • Visualization
Model monitoring is the process of continuously tracking the performance and behavior of a deployed machine learning model. It involves checking for deviations, evaluating predictions against real-world data, and ensuring that the model remains accurate and reliable over time. Monitoring is crucial for maintaining model quality in production.
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