Exam DP-100 topic 2 question 116 discussion

Actual exam question from Microsoft's DP-100

Question #: 116
Topic #: 2

You manage an Azure Machine Learning workspace. You have a folder that contains a CSV file. The folder is registered as a folder data asset.

You plan to use the folder data asset for data wrangling during interactive development.

You need to access and load the folder data asset into a Pandas data frame.

Which method should you use to achieve this goal?

A. mltable.from_parquet_files()
B. mltable.from_delimited_files()
C. mltable.from_data_lake()
D. mltable.load()

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Suggested Answer: B 🗳️

by nicorg5 at March 12, 2024, 9:49 a.m.

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445f1bd

1 month, 3 weeks ago

Selected Answer: D

Is load() guys. Check this ... # load mltable from azureml data asset short uri from mltable import load from azure.ai.ml import MLClient from azure.identity import DefaultAzureCredential credential = DefaultAzureCredential() ml_client = MLClient(credential, <subscription_id>, <resourcegroup-name>, <workspace-name>) tbl = load('azureml:<data-asset-name>:<version>', ml_client=ml_client) in this link https://learn.microsoft.com/en-us/python/api/mltable/mltable?view=azure-ml-py#mltable-from-delimited-files

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