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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q242-Q247):

NEW QUESTION # 242
You need to configure the Edit Metadata module so that the structure of the datasets match.
Which configuration options should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 243
You manage an Azure Machine Learning workspace. You configure an automated machine learning regression training job by using the Azure Machine Learning Python SDK v2. You configure the regression job by using the following script:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

Answer:

Explanation:

Explanation:

NEW QUESTION # 244
You are analyzing a dataset containing historical data from a local taxi company. You arc developing a regression a regression model.
You must predict the fare of a taxi trip.
You need to select performance metrics to correctly evaluate the- regression model.
Which two metrics can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. an F 1 score that is low.
B. an R-Squared value close to 0
C. an F1 score that is high
D. a Root Mean Square Error value that is high
E. an R Squared value dose to 1
F. a Root Mean Square Error value that is low

Answer: E,F

Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model

NEW QUESTION # 245
You create an Azure Machine Learning workspace.
You must use the Python SDK v2 to implement an experiment from a Jupyter notebook in the workspace. The experiment must log a list of numeral metrics.
You need to implement a method to log a list of numeral metrics.
Which method should you use?

A. mlflow.log_artifact()
B. mlflow.log.batch()
C. mlflow.log_metric()
D. mlflow.log_image()

Answer: C

Explanation:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-view-metrics?view=azureml- api-2&tabs=interactive#logging-metrics

NEW QUESTION # 246
An organization uses Azure Machine Learning service and wants to expand their use of machine learning.
You have the following compute environments. The organization does not want to create another compute environment.

You need to determine which compute environment to use for the following scenarios.
Which compute types should you use? To answer, drag the appropriate compute environments to the correct scenarios. Each compute environment may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-set-up-training-targets

NEW QUESTION # 247
......

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