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Microsoft Updated DP-100 Exam Questions and Answers by deacon

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Microsoft DP-100 Exam Overview :

Exam Name: Designing and Implementing a Data Science Solution on Azure
Exam Code: DP-100 Dumps
Vendor: Microsoft Certification: Microsoft Azure
Questions: 460 Q&A's Shared By: deacon
Question 28

You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder.

The experiment fails.

You need to troubleshoot the failed experiment.

What are two possible ways to achieve this goal? Each correct answer presents a complete solution.

Options:

A.

Use the get_metrics() method of the run object to retrieve the experiment run logs.

B.

Use the get_details_with_logs() method of the run object to display the experiment run logs.

C.

View the log files for the experiment run in the experiment folder.

D.

View the logs for the experiment run in Azure Machine Learning studio.

E.

Use the get_output() method of the run object to retrieve the experiment run logs.

Discussion
Question 29

You are creating a binary classification by using a two-class logistic regression model.

You need to evaluate the model results for imbalance.

Which evaluation metric should you use?

Options:

A.

Relative Absolute Error

B.

AUC Curve

C.

Mean Absolute Error

D.

Relative Squared Error

Discussion
Question 30

You have a Python script that executes a pipeline. The script includes the following code:

from azureml.core import Experiment

pipeline_run = Experiment(ws, 'pipeline_test').submit(pipeline)

You want to test the pipeline before deploying the script.

You need to display the pipeline run details written to the STDOUT output when the pipeline completes.

Which code segment should you add to the test script?

Options:

A.

pipeline_run.get.metrics()

B.

pipeline_run.wait_for_completion(show_output=True)

C.

pipeline_param = PipelineParameter(name="stdout",default_value="console")

D.

pipeline_run.get_status()

Discussion
Question 31

You manage are Azure Machine Learning workspace by using the Python SDK v2.

You must create an automated machine learning job to generate a classification model by using data files stored in Parquet format. You must configure an auto scaling compute target and a data asset for the job.

You need to configure the resources for the job.

Which resource configuration should you use? to answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Questions 31

Options:

Discussion
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