Free Microsoft DP-100 Practice Exam with Questions & Answers | Set: 3

You need to define an evaluation strategy for the crowd sentiment models.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts. Data processed by the first step is passed to the second step.

You must update the content of the downstream data source of pipeline 1 and run the pipeline again.

You need to ensure the new run of pipeline 1 fully processes the updated content.

Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps.

Does the solution meet the goal'

You are using the Hyperdrive feature in Azure Machine Learning to train a model.

You configure the Hyperdrive experiment by running the following code:

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

NOTE: Each correct selection is worth one point.

You configure a Deep Learning Virtual Machine for Windows.

You need to recommend tools and frameworks to perform the following:

Build deep neural network (DNN) models

Perform interactive data exploration and visualization

Which tools and frameworks should you recommend? To answer, drag the appropriate tools to the correct tasks. Each tool 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.

You create an Azure Machine Learning workspace named ML-workspace. You also create an Azure Databricks workspace named DB-workspace. DB-workspace contains a cluster named DB-cluster.

You must use DB-cluster to run experiments from notebooks that you import into DB-workspace.

You need to use ML-workspace to track MLflow metrics and artifacts generated by experiments running on DB-cluster. The solution must minimize the need for custom code.

What should you do?

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 are creating a new experiment in Azure Learning learning Studio.

One class has a much smaller number of observations than the other classes in the training

You need to select an appropriate data sampling strategy to compensate for the class imbalance.

Solution: You use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.

Does the solution meet the goal?

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 create an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:

• /data/2018/Q1 .csv

• /data/2018/Q2.csv

• /data/2018/Q3.csv

• /data/2018/Q4.csv

• /data/2019/Q1.csv

All files store data in the following format:

id,M,f2,l

1,1,2,0

2,1,1,1

32,10

You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

Solution: Run the following code:

Does the solution meet the goal?

You create a workspace to include a compute instance by using Azure Machine Learning Studio. You are developing a Python SDK v2 notebook in the workspace. You need to use Intellisense in the notebook. What should you do?

You need to implement a scaling strategy for the local penalty detection data.

Which normalization type should you use?

You need to define a modeling strategy for ad response.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.