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Actual exam question for Microsoft's AI-300 exam Question #: 58 Topic #: 1
You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2. You create a General Purpose v2 Azure storage account named mlstorage 1. The storage account includes a publicly accessible container named mlcontainer 1. The container stores 10 blobs with files in the CSV format. You must develop Python SDK v2 code to create a data asset referencing all blobs in the container named mlcontainer 1. You need to complete the Python SDK v2 code. How should you complete the code? To answer, select the appropriate options in the answer area . NOTE: Each correct selection is worth one point.
Suggested Answer:
Explanation: Because you want to reference all blobs in a container rather than a single file, the correct asset type is AssetTypes.URI_FOLDER. This type points to a directory-level URI, allowing Azure ML to traverse all files within it. For a publicly accessible Azure Blob Storage container, the URI follows the pattern https://storage_account.blob.core.windows.net/container_name/. You then create the Data object with the correct type, path, name, and version parameters, and register it in the workspace using ml_client.data. create_or_update. Do not use AssetTypes.URI_FILE, which references a single file. Do not use AssetTypes. MLTABLE unless you have an MLTable YAML descriptor. URI_FOLDER is the correct choice for referencing a collection of CSV blobs in an Azure Blob Storage container, allowing Azure ML to discover and process all files within the specified path. Microsoft Learn Reference Topic: Create and manage data assets in Azure Machine Learning Python SDK v2 - URI_FOLDER
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