Microsoft Certified Azure Data Scientist Associate - DP-100
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Ultimate access to all questions.
You plan to run a Python script as an Azure Machine Learning experiment. The script contains the following code:
from azureml.core import Dataset, Run
run = Run.get_context()
ds = run.input_datasets['images']
from azureml.core import Dataset, Run
run = Run.get_context()
ds = run.input_datasets['images']
You must specify a file dataset as an input to the script. The dataset consists of multiple large image files and must be streamed directly from its source.
You need to write code to define a ScriptRunConfig object for the experiment and pass the ds dataset as an argument.
Which code segment should you use?
A
arguments = ['--input-data', ds.to_pandas_dataframe()]
B
arguments = ['--input-data', ds.as_mount()]_
C
arguments = ['--data-data', ds]
D
arguments = ['--input-data', ds.as_download()]_