Microsoft Exam DP-100 Topic 10 Question 46 Discussion

Actual exam question for Microsoft's DP-100 exam

Question #: 46
Topic #: 10

You use the Azure Machine Learning designer to create and run a training pipeline.

The pipeline must be run every night to inference predictions from a large volume of files. The folder where the files will be stored is defined as a dataset.

You need to publish the pipeline as a REST service that can be used for the nightly inferencing run.

What should you do?

ACreate a batch inference pipeline

BSet the compute target for the pipeline to an inference cluster

CCreate a real-time inference pipeline

DClone the pipeline

Show Suggested Answer

Suggested Answer: A

Azure Machine Learning Batch Inference targets large inference jobs that are not time-sensitive. Batch Inference provides cost-effective inference compute scaling, with unparalleled throughput for asynchronous applications. It is optimized for high-throughput, fire-and-forget inference over large collections of data.

You can submit a batch inference job by pipeline_run, or through REST calls with a published pipeline.

https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/parallel-run/README.md

by Billye at May 06, 2022, 05:32 PM

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