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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 51 discussion

A company has deployed an ML model that detects fraudulent credit card transactions in real time in a banking application. The model uses Amazon SageMaker Asynchronous Inference. Consumers are reporting delays in receiving the inference results.
An ML engineer needs to implement a solution to improve the inference performance. The solution also must provide a notification when a deviation in model quality occurs.
Which solution will meet these requirements?

  • A. Use SageMaker real-time inference for inference. Use SageMaker Model Monitor for notifications about model quality.
  • B. Use SageMaker batch transform for inference. Use SageMaker Model Monitor for notifications about model quality.
  • C. Use SageMaker Serverless Inference for inference. Use SageMaker Inference Recommender for notifications about model quality.
  • D. Keep using SageMaker Asynchronous Inference for inference. Use SageMaker Inference Recommender for notifications about model quality.
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Suggested Answer: A 🗳️

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Saransundar
1 month, 2 weeks ago
Selected Answer: A
Sagemaker Real-Time Inference - Faster predictions to solve delay issues; Model Monitor to tracks model quality and sends alerts for deviations
upvoted 2 times
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GiorgioGss
1 month, 3 weeks ago
Selected Answer: A
The delay comes from using an async inference.
upvoted 1 times
...
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