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DP-100 Sample Questions Answers

Questions 4

You have an Azure Machine Learning workspace.

You plan to run a job to tram a model as an MLflow model output.

You need to specify the output mode of the MLflow model.

Which three modes can you specify? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

rw_mount

B.

ro mount

C.

upload

D.

download

E.

direct

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Questions 5

You deploy a real-time inference service for a trained model.

The deployed model supports a business-critical application, and it is important to be able to monitor the data submitted to the web service and the predictions the data generates.

You need to implement a monitoring solution for the deployed model using minimal administrative effort.

What should you do?

Options:

A.

View the explanations for the registered model in Azure ML studio.

B.

Enable Azure Application Insights for the service endpoint and view logged data in the Azure portal.

C.

Create an ML Flow tracking URI that references the endpoint, and view the data logged by ML Flow.

D.

View the log files generated by the experiment used to train the model.

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Questions 6

You write code to retrieve an experiment that is run from your Azure Machine Learning workspace.

The run used the model interpretation support in Azure Machine Learning to generate and upload a model explanation.

Business managers in your organization want to see the importance of the features in the model.

You need to print out the model features and their relative importance in an output that looks similar to the following.

How should you complete the code? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 7

You create an Azure Machine Learning workspace named woricspace1. The workspace contains a Python SDK v2 notebook that uses MLflow to collect model training metrics and artifacts from your local computer.

You must reuse the notebook to run on Azure Machine Learning compute instance in workspace1.

You need to continue to log metrics and artifacts from your data science code.

What should you do?

Options:

A.

Configure the tracking URI.

B.

Instantiate the job class.

C.

Log into workspace"!.

D.

Instantiate the MLCIient class.

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Questions 8

You create a binary classification model.

You need to evaluate the model performance.

Which two metrics can you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

relative absolute error

B.

precision

C.

accuracy

D.

mean absolute error

E.

coefficient of determination

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Questions 9

You have an Azure Machine Learning workspace that contains a CPU-based compute cluster and an Azure Kubernetes Services (AKS) inference cluster. You create a tabular dataset containing data that you plan to use to create a classification model.

You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a 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.

Options:

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Questions 10

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.

An IT department creates the following Azure resource groups and resources:

The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace. You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.

You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.

Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace. Run the training script as an experiment on the aks-cluster compute target.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

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Questions 11

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 model to predict the price of a student’s artwork depending on the following variables: the student’s length of education, degree type, and art form.

You start by creating a linear regression model.

You need to evaluate the linear regression model.

Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error, Relative Squared Error, and the Coefficient of Determination.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

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Questions 12

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.

An IT department creates the following Azure resource groups and resources:

The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.

You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.

You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.

Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on local compute.

Options:

A.

Yes

B.

No

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Questions 13

You need to obtain the output from the pipeline execution. Where will you find the output?

Options:

A.

the Activity Log in the Azure portal for the Machine Learning workspace

B.

a file named parallel_run_step.txt located in the output folder

C.

the digitjdentification.py script

D.

the Inference Clusters tab in Machine Learning studio

E.

the debug log

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Questions 14

You have a binary classifier that predicts positive cases of diabetes within two separate age groups.

The classifier exhibits a high degree of disparity between the age groups.

You need to modify the output of the classifier to maximize its degree of fairness across the age groups and meet the following requirements:

• Eliminate the need to retrain the model on which the classifier is based.

• Minimize the disparity between true positive rates and false positive rates across age groups.

Which algorithm and panty constraint should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Options:

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Questions 15

You need to identify the methods for dividing the data according, to the testing requirements.

Which properties should you select? To answer, select the appropriate option-, m the answer area. NOTE: Each correct selection is worth one point.

Options:

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Questions 16

You are solving a classification task.

The dataset is imbalanced.

You need to select an Azure Machine Learning Studio module to improve the classification accuracy.

Which module should you use?

Options:

A.

Fisher Linear Discriminant Analysis.

B.

Filter Based Feature Selection

C.

Synthetic Minority Oversampling Technique (SMOTE)

D.

Permutation Feature Importance

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Questions 17

You need to select a feature extraction method.

Which method should you use?

Options:

A.

Mutual information

B.

Mood’s median test

C.

Kendall correlation

D.

Permutation Feature Importance

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Questions 18

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.

Options:

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Questions 19

You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets.

How should you configure the module properties? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 20

You need to set up the Permutation Feature Importance module according to the model training requirements.

Which properties should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 21

You need to identify the methods for dividing the data according to the testing requirements.

Which properties should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 22

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:

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Questions 23

You build a data pipeline in an Azure Machine Learning workspace by using the Azure Machine Learning SDK for Python.

You need to run a Python script as a pipeline step.

Which two classes could you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

PythonScriptStep

B.

AutoMLStep

C.

CommandStep

D.

StepRun

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Questions 24

You need to replace the missing data in the AccessibilityToHighway columns.

How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 25

You need to select a feature extraction method.

Which method should you use?

Options:

A.

Spearman correlation

B.

Mutual information

C.

Mann-Whitney test

D.

Pearson’s correlation

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Questions 26

You need to correct the model fit issue.

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.

Options:

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Questions 27

You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed.

Which three Azure Machine Learning Studio modules should you use in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Options:

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Questions 28

You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements.

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

Options:

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Questions 29

You need to select an environment that will meet the business and data requirements.

Which environment should you use?

Options:

A.

Azure HDInsight with Spark MLlib

B.

Azure Cognitive Services

C.

Azure Machine Learning Studio

D.

Microsoft Machine Learning Server

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Questions 30

You need to implement early stopping criteria as suited in the model training requirements.

Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Options:

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Questions 31

You need to implement a new cost factor scenario for the ad response models as illustrated in the

performance curve exhibit.

Which technique should you use?

Options:

A.

Set the threshold to 0.5 and retrain if weighted Kappa deviates +/- 5% from 0.45.

B.

Set the threshold to 0.05 and retrain if weighted Kappa deviates +/- 5% from 0.5.

C.

Set the threshold to 0.2 and retrain if weighted Kappa deviates +/- 5% from 0.6.

D.

Set the threshold to 0.75 and retrain if weighted Kappa deviates +/- 5% from 0.15.

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Questions 32

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.

Options:

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Questions 33

You need to use the Python language to build a sampling strategy for the global penalty detection models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 34

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.

Options:

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Questions 35

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.

Options:

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Questions 36

You need to define a process for penalty event detection.

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.

Options:

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Questions 37

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

Which normalization type should you use?

Options:

A.

Streaming

B.

Weight

C.

Batch

D.

Cosine

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Questions 38

You need to implement a feature engineering strategy for the crowd sentiment local models.

What should you do?

Options:

A.

Apply an analysis of variance (ANOVA).

B.

Apply a Pearson correlation coefficient.

C.

Apply a Spearman correlation coefficient.

D.

Apply a linear discriminant analysis.

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Questions 39

You need to modify the inputs for the global penalty event model to address the bias and variance issue.

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.

Options:

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Questions 40

You need to resolve the local machine learning pipeline performance issue. What should you do?

Options:

A.

Increase Graphic Processing Units (GPUs).

B.

Increase the learning rate.

C.

Increase the training iterations,

D.

Increase Central Processing Units (CPUs).

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Questions 41

You need to build a feature extraction strategy for the local models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

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Questions 42

You need to define a process for penalty event detection.

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.

Options:

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Questions 43

You need to implement a model development strategy to determine a user’s tendency to respond to an ad.

Which technique should you use?

Options:

A.

Use a Relative Expression Split module to partition the data based on centroid distance.

B.

Use a Relative Expression Split module to partition the data based on distance travelled to the event.

C.

Use a Split Rows module to partition the data based on distance travelled to the event.

D.

Use a Split Rows module to partition the data based on centroid distance.

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Exam Code: DP-100
Exam Name: Designing and Implementing a Data Science Solution on Azure
Last Update: Oct 8, 2024
Questions: 428
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