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Answer: Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine Learning service.
The question requires accessing 100,000 JPG bird photographs from an Azure blob container in an Azure Machine Learning workspace while minimizing data movement. Option D (Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine Learning service) is optimal because it allows direct access to the existing blob storage without copying or moving data, aligning with the requirement to minimize data movement. This approach leverages Azure ML's datastore feature to reference external storage, which is efficient for large datasets like 100,000 images. Option A involves unnecessary data transfer to a new Data Lake store. Option B is unsuitable as Cosmos DB is for structured data, not image files. Option C is incorrect because TabularDataset is for tabular data, not image data (FileDataset should be used for images). Option E requires copying data to an existing blob datastore, which involves data movement and contradicts the minimization requirement. The community discussion strongly supports D with 100% consensus and upvotes, noting it has the 'lowest movement' and is correct on recent exams.
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You are creating a multi-class image classification deep learning model for tracking bird health and migration. You have 100,000 JPG format bird photographs stored in an Azure blob container. You need to access these files from your Azure Machine Learning service workspace for model training while minimizing 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.
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