Topic 1 Question 62
A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately. Which Amazon SageMaker inference option will meet these requirements?
Batch transform
Real-time inference
Serverless inference
Asynchronous inference
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コメント(6)
- 正解だと思う選択肢: A
Batch transform is specifically designed to handle large volumes of data, including datasets that are multiple GBs in size. This aligns perfectly with the company's requirement to perform inference on large datasets.
👍 3Blair772024/11/12 - 正解だと思う選択肢: D
asynchronous inference is the most appropriate choice for the company's specific needs, as it provides a balance between processing large datasets and not requiring immediate results.
👍 2viejito2025/01/09 - 正解だと思う選択肢: A
Info on Batch Transform matches up with the details of 'large datsets' and 'don't need projections immediately. https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html
👍 1GriffXX2024/11/11
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