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Answer: as_download(), as_mount()
The question requires selecting two modes for accessing a dataset with hierarchical folder structure in Azure ML. Based on Azure ML documentation and community consensus (with multiple comments confirming B and D, including highly upvoted responses), the correct modes are as_download() and as_mount(). as_download() downloads the dataset files to the compute target, while as_mount() mounts the dataset as a virtual file system. Both support hierarchical folder structures. to_pandas_dataframe() is not a valid dataset mode but a method for tabular data conversion, and as_upload() is not a valid Azure ML dataset method.
Author: LeetQuiz Editorial Team
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You are preparing to execute a Python script as an Azure Machine Learning experiment. The script is required to read files from a hierarchical folder structure, which will be provided to the script as a dataset input argument.
You need to select a suitable mode for this dataset argument. Which two modes should you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A
to_pandas_dataframe()
B
as_download()
C
as_upload()
D
as_mount()
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