DP-100 · Question #323
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…
The correct answer is A. Yes. The solution DOES meet the goal. Registering the model in the workspace is the required prerequisite for deploying it to a batch endpoint. Azure Machine Learning batch endpoints can only deploy models that are registered in the workspace's model registry. Once the MLflow model…
Question
Options
- AYes
- BNo
How the community answered
(48 responses)- A92% (44)
- B8% (4)
Explanation
The solution DOES meet the goal. Registering the model in the workspace is the required prerequisite for deploying it to a batch endpoint. Azure Machine Learning batch endpoints can only deploy models that are registered in the workspace's model registry. Once the MLflow model cloned from the local repository is registered, it becomes available as a deployable asset that can be referenced in a batch deployment configuration.
Topics
Community Discussion
No community discussion yet for this question.