DP-100 · Question #143
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 photograph
The correct answer is D. Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine. Registering the existing Azure blob storage as a datastore in Azure ML creates a logical reference (connection) to the blob container-no data is moved. The training code then accesses images directly from the original location. Option A (Azure Data Lake) and Option E (copy to ML
Question
Options
- ACreate an Azure Data Lake store and move the bird photographs to the store.
- BCreate an Azure Cosmos DB database and attach the Azure Blob containing bird photographs
- CCreate and register a dataset by using TabularDataset class that references the Azure blob
- DRegister the Azure blob storage containing the bird photographs as a datastore in Azure Machine
- ECopy the bird photographs to the blob datastore that was created with your Azure Machine
How the community answered
(39 responses)- A5% (2)
- C3% (1)
- D79% (31)
- E13% (5)
Explanation
Registering the existing Azure blob storage as a datastore in Azure ML creates a logical reference (connection) to the blob container-no data is moved. The training code then accesses images directly from the original location. Option A (Azure Data Lake) and Option E (copy to ML blob datastore) both require moving 100,000 photos. Option B (Cosmos DB) is a NoSQL database and inappropriate for storing image files. Option C uses TabularDataset, which is designed for structured/tabular data, not image files; images require a FileDataset. Registering the datastore (D) satisfies both requirements: access from the workspace and zero data movement.
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