Answer-first summary for fast verification
Answer: No
The solution does not meet the goal because simply adding another compute resource to the workspace is insufficient for deploying an MLflow model to a batch endpoint. According to Azure ML best practices and the community discussion consensus (100% selected B), the key missing steps are: 1) Registering the MLflow model in the Azure ML workspace, and 2) Creating or configuring the batch endpoint to use the registered model. The workspace already has an AmlCompute cluster and batch endpoint, so adding another compute resource does not address the core requirements for model deployment. The community comments emphasize that model registration and batch endpoint configuration are necessary.
Author: LeetQuiz Editorial Team
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You have an Azure Machine Learning workspace containing an AmlCompute cluster and a batch endpoint. You clone a repository with an MLflow model to your local computer.
You need to deploy the model to the batch endpoint.
Solution: Add a compute resource to the workspace.
Does the solution meet the goal?
A
Yes
B
No
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