Which module should you add to the pipeline in Designer?

You are creating a new Azure Machine Learning pipeline using the designer.

The pipeline must train a model using data in a comma-separated values (CSV) file that is published on a

website. You have not created a dataset for this file.

You need to ingest the data from the CSV file into the designer pipeline using the minimal administrative effort.

Which module should you add to the pipeline in Designer?
A . Convert to CSV
B . Enter Data Manually
D
C . Import Data
D . Dataset

View Answer

Answer: D

Explanation:

The preferred way to provide data to a pipeline is a Dataset object. The Dataset object

points to data that lives in or is accessible from a datastore or at a Web URL. The Dataset

class is abstract, so you will create an instance of either a FileDataset (referring to one or

more files) or a TabularDataset that’s created by from one or more files with delimited

columns of data.

Example:

from azureml.core import Dataset

iris_tabular_dataset = Dataset.Tabular.from_delimited_files([(def_blob_store, ‘train-dataset/iris.csv’)])

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-your-first-pipeline