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DP-100 Exam Dumps : Designing and Implementing a Data Science Solution on Azure

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Designing and Implementing a Data Science Solution on Azure Questions and Answers

Question 1

You create a script that trains a convolutional neural network model over multiple epochs and logs the validation loss after each epoch. The script includes arguments for batch size and learning rate.

You identify a set of batch size and learning rate values that you want to try.

You need to use Azure Machine Learning to find the combination of batch size and learning rate that results in the model with the lowest validation loss.

What should you do?

Options:

A.

Run the script in an experiment based on an AutoMLConfig object

B.

Create a PythonScriptStep object for the script and run it in a pipeline

C.

Use the Automated Machine Learning interface in Azure Machine Learning studio

D.

Run the script in an experiment based on a ScriptRunConfig object

E.

Run the script in an experiment based on a HyperDriveConfig object

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Question 2

You need to configure the Permutation Feature Importance module for the model training requirements.

What should you do? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 3

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Delete the Python 3.8 - AzureML kernel.

Does the solution meet the goal?

Options:

A.

Yes

B.

No