Answer-first summary for fast verification
Answer: Yes
The solution meets the goal because registering the MLflow model in the Azure Machine Learning workspace is a required step before deploying to a batch endpoint. The community discussion unanimously supports this with 100% of answers selecting 'Yes' and detailed comments explaining that model registration is necessary to reference the model during deployment. Once registered, the model can be deployed to the batch endpoint using the existing AmlCompute cluster. No additional steps are needed at this stage since the batch endpoint and compute cluster already exist.
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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: Register the model in the workspace.
Does the solution meet the goal?
A
Yes
B
No