You create a deep learning model for image recognition on Azure Machine Learning service using GPU-based training.
You must deploy the model to a context that allows for real-time GPU-based inferencing.
You need to configure compute resources for model inferencing.
Which compute type should you use?

A. Azure Container Instance

B. Azure Kubernetes Service

C. Field Programmable Gate Array

D. Machine Learning Compute








 

Suggested Answer: B

You can use Azure Machine Learning to deploy a GPU-enabled model as a web service. Deploying a model on Azure Kubernetes Service (AKS) is one option.
The AKS cluster provides a GPU resource that is used by the model for inference.
Inference, or model scoring, is the phase where the deployed model is used to make predictions. Using GPUs instead of CPUs offers performance advantages on highly parallelizable computation.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-inferencing-gpus

This question is in DP-100 Exam
For getting Microsoft Azure Data Scientist Associate Certificate


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