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MLS-C01 · Question #363

MLS-C01 Question #363: Real Exam Question with Answer & Explanation

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Machine Learning Implementation and Operations

Question

A media company wants to deploy a machine learning (ML) model that uses Amazon SageMaker to recommend new articles to the company's readers. The company's readers are primarily located in a single city. The company notices that the heaviest reader traffic predictably occurs early in the morning, after lunch, and again after work hours. There is very little traffic at other times of day. The media company needs to minimize the time required to deliver recommendations to its readers. The expected amount of data that the API call will return for inference is less than 4 MB. Which solution will meet these requirements in the MOST cost-effective way?

Options

  • AReal-time inference with auto scaling
  • BServerless inference with provisioned concurrency
  • CAsynchronous inference
  • DA batch transform task

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Topics

#SageMaker Inference#Serverless ML#Low Latency#Cost Optimization
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