Topic 1 Question 51
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?
Use SageMaker real-time inference for inference. Use SageMaker Model Monitor for notifications about model quality.
Use SageMaker batch transform for inference. Use SageMaker Model Monitor for notifications about model quality.
Use SageMaker Serverless Inference for inference. Use SageMaker Inference Recommender for notifications about model quality.
Keep using SageMaker Asynchronous Inference for inference. Use SageMaker Inference Recommender for notifications about model quality.
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コメント(2)
- 正解だと思う選択肢: A
Sagemaker Real-Time Inference - Faster predictions to solve delay issues; Model Monitor to tracks model quality and sends alerts for deviations
👍 2Saransundar2024/12/04 - 正解だと思う選択肢: A
The delay comes from using an async inference.
👍 1GiorgioGss2024/11/27
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