What should you do?

You are a lead data scientist for a project that tracks the health and migration of birds. You create a multi-class image classification deep learning model that uses a set of labeled bird photographs collected by experts.

You have 100,000 photographs of birds. All photographs use the JPG format and are stored in an Azure blob container in an Azure subscription.

You need to access the bird photograph files in the Azure blob container from the Azure Machine Learning service workspace that will be used for deep learning model training. You must minimize data movement.

What should you do?
A . Create an Azure Data Lake store and move the bird photographs to the store.
B . Create an Azure Cosmos DB database and attach the Azure Blob containing bird photographs storage to the database.
C . Create and register a dataset by using TabularDataset class that references the Azure blob storage
containing bird photographs.
D . Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine Learning service.
E . Copy the bird photographs to the blob datastore that was created with your Azure Machine Learning service workspace.

Answer: D

Explanation:

We recommend creating a datastore for an Azure Blob container. When you create a workspace, an Azure blob container and an Azure file share are automatically registered to the workspace.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-access-data

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