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MLS-C01 · Question #287

MLS-C01 Question #287: Real Exam Question with Answer & Explanation

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Machine Learning Implementation and Operations

Question

A financial services company wants to automate its loan approval process by building a machine learning (ML) model. Each loan data point contains credit history from a third-party data source and demographic information about the customer. Each loan approval prediction must come with a report that contains an explanation for why the customer was approved for a loan or was denied for a loan. The company will use Amazon SageMaker to build the model. Which solution will meet these requirements with the LEAST development effort?

Options

  • AUse SageMaker Model Debugger to automatically debug the predictions, generate the
  • BUse AWS Lambda to provide feature importance and partial dependence plots. Use the plots to
  • CUse SageMaker Clarify to generate the explanation report. Attach the report to the predicted
  • DUse custom Amazon CloudWatch metrics to generate the explanation report. Attach the report to

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Topics

#Machine Learning Explainability#Amazon SageMaker Clarify#Model Interpretability#MLOps
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