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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #171

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #171: Real Exam Question with Answer & Explanation

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Submitted by marco_it· Apr 18, 2026Monitoring, optimizing, and maintaining ML solutions

Question

You work for a magazine distributor and need to build a model that predicts which customers will renew their subscriptions for the upcoming year. Using your company's historical data as your training set, you created a TensorFlow model and deployed it to Vertex AI. You need to determine which customer attribute has the most predictive power for each prediction served by the model. What should you do?

Options

  • AStream prediction results to BigQuery. Use BigQuery's CORR(X1, X2) function to calculate the
  • BUse Vertex Explainable AI. Submit each prediction request with the explain' keyword to retrieve
  • CUse Vertex AI Workbench user-managed notebooks to perform a Lasso regression analysis on
  • DUse the What-If tool in Google Cloud to determine how your model will perform when individual

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Topics

#Vertex Explainable AI#Feature attribution#Model explainability#Google Cloud ML
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