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AIF-C01 · Question #309

A company is monitoring a predictive model by using Amazon SageMaker Model Monitor. The company notices data drift beyond a defined threshold. The company wants to mitigate a potentially adverse…

The correct answer is C. Re-train the model with fresh data. When Amazon SageMaker Model Monitor detects data drift beyond a defined threshold, it indicates that the current data differs from what the model was trained on. Retraining the model with recent data ensures it adapts to new patterns and maintains predictive accuracy.

Submitted by javi_es· Mar 30, 2026

Question

A company is monitoring a predictive model by using Amazon SageMaker Model Monitor. The company notices data drift beyond a defined threshold. The company wants to mitigate a potentially adverse impact on the predictive model. Which solution will meet these requirements?

Options

  • ARestart the SageMaker AI endpoint.
  • BAdjust the monitoring sensitivity.
  • CRe-train the model with fresh data.
  • DSet up experiments tracking.

How the community answered

(41 responses)
  • A
    5% (2)
  • B
    10% (4)
  • C
    83% (34)
  • D
    2% (1)

Explanation

When Amazon SageMaker Model Monitor detects data drift beyond a defined threshold, it indicates that the current data differs from what the model was trained on. Retraining the model with recent data ensures it adapts to new patterns and maintains predictive accuracy.

Topics

#SageMaker Model Monitor#data drift#model retraining

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