A manufacturing company wants to monitor its devices for anomalous behavior. A data scientist has trained an Amazon SageMaker scikit-learn model that classifies a device as normal or anomalous based on its 4-day telemetry. The 4-day telemetry of each device is collected in a separate file and is placed in an Amazon S3 bucket once every hour. The total time to run the model across the telemetry for all devices is 5 minutes.
What is the MOST cost-effective solution for the company to use to run the model across the telemetry for all the devices?

A. SageMaker Batch Transform

B. SageMaker Asynchronous Inference

C. SageMaker Processing

D. A SageMaker multi-container endpoint








 

Suggested Answer: C

Community Answer: A




This question is in MLS-C01 AWS Certified Machine Learning – Specialty Exam
For getting AWS Certified Machine Learning – Specialty Certificate


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