Exam DP-100 topic 3 question 125 discussion

https://learn.microsoft.com/en-us/python/api/mltable/mltable.mltable.mltable?source=recommendations&view=azure-ml-py A MLTable defines a series of lazily-evaluated, immutable operations to load data from the data source.

D is the right answer.

Selected Answer: D

lazy evaluation==>MLtable

A. MLTable In order to provide training data to AutoML in SDK v2 you need to upload it into the cloud through an MLTable. Requirements for loading data into an MLTable: • Data must be in tabular form. • The value to predict, target column, must be in the data. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-auto-train?view=azureml-api-2&tabs=python

Answer should be C

C To load data into a Pandas dataframe for use with AutoMLjobs in Azure Machine Learning, you should use the Datastore concept. C. Datastore A Datastore in Azure Machine Learning is a way to store, access, and manage data securely. It allows you to connect to various data storage options, including Azure Blob Storage, Azure SQL Database, and more. Datastores are commonly used for accessing and managing datasets in Azure Machine Learning. You can use the Datastore to load your tabular text files into a Pandas dataframe, and it supports lazy evaluation, meaning data is loaded only when needed, which is useful for working with large datasets efficiently. Options A, B, and D are not the primary mechanisms for loading data into a Pandas dataframe within the context of Azure Machine Learning.

Answer should be C. Datastore