What should you do?

You create an Azure Machine Learning workspace named ML-workspace. You also create an Azure Databricks workspace named DB-workspace. DB-workspace contains a cluster named DB-cluster.

You must use DB-cluster to run experiments from notebooks that you import into DB-workspace.

You need to use ML-workspace to track MLflow metrics and artifacts generated by experiments running on DB-cluster. The solution must minimize the need for custom code.

What should you do?
A . From DB-cluster, configure the Advanced Logging option.
B . From DB-workspace. configure the Link Azure ML workspace option.
C . From ML-workspace. create an attached compute.
D . From ML-workspace. create a compute cluster.

Answer: B

Explanation:

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-databricks