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Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure Exam Practice Test

Demo: 43 questions
Total 428 questions

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

Question 1

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 2

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:

Question 3

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

Question 4

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:

Question 5

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:

Question 6

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:

Question 7

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:

Question 8

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:

Question 9

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:

Question 10

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:

Question 11

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

Question 12

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:

Question 13

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:

Question 14

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:

Question 15

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.

Question 16

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:

Question 17

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:

Question 18

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.

Question 19

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

Question 20

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:

Question 21

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

Question 22

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:

Question 23

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).

Question 24

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:

Question 25

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:

Question 26

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.

Question 27

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:

Question 28

You create a binary classification model by using Azure Machine Learning Studio.

You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:

    iterate all possible combinations of hyperparameters

    minimize computing resources required to perform the sweep

    You need to perform a parameter sweep of the model.

Which parameter sweep mode should you use?

Options:

A.

Random sweep

B.

Sweep clustering

C.

Entire grid

D.

Random grid

E.

Random seed

Question 29

You are using a Git repository to track work in an Azure Machine Learning workspace.

You need to authenticate a Git account by using SSH.

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:

Question 30

You are developing a machine learning solution by using the Azure Machine Learning designer.

You need to create a web service that applications can use to submit data feature values and retrieve a predicted label.

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:

Question 31

You create a binary classification model to predict whether a person has a disease.

You need to detect possible classification errors.

Which error type should you choose for each description? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 32

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 plan to use a Python script to run an Azure Machine Learning experiment. The script creates a reference to the experiment run context, loads data from a file, identifies the set of unique values for the label column, and completes the experiment run:

The experiment must record the unique labels in the data as metrics for the run that can be reviewed later.

You must add code to the script to record the unique label values as run metrics at the point indicated by the comment.

Solution: Replace the comment with the following code:

run.log_list('Label Values', label_vals)

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 33

You train and register an Azure Machine Learning model

You plan to deploy the model to an online endpoint

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution:

Create a managed online endpoint with the default authentication settings. Deploy the model to the online endpoint.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 34

You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace. You add code that imports all relevant Python libraries.

You must configure Bayesian sampling over the search space for the num_hidden_layers and batch_size hyperparameters.

You need to complete the following Python code to configure Bayesian sampling.

Which code segments should you use? To answer, select the appropriate options in the answer area

NOTE: Each correct selection is worth one point.

Options:

Question 35

You create a multi-class image classification deep learning model.

You train the model by using PyTorch version 1.2.

You need to ensure that the correct version of PyTorch can be identified for the inferencing environment when the model is deployed.

What should you do?

Options:

A.

Save the model locally as a.pt file, and deploy the model as a local web service.

B.

Deploy the model on computer that is configured to use the default Azure Machine Learning conda

environment.

C.

Register the model with a .pt file extension and the default version property.

D.

Register the model, specifying the model_framework and model_framework_version properties.

Question 36

You create an Azure Machine Learning pipeline named pipeline1 with two steps that contain Python scripts. Data processed by the first step is passed to the second step.

You must update the content of the downstream data source of pipeline1 and run the pipeline again

You need to ensure the new run of pipeline1 fully processes the updated content.

Solution: Set the allow_reuse parameter of the PythonScriptStep object of both steps to False

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 37

You manage an Azure Machine Learning workspace. The development environment tor managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks A Synapse Spark Compute is currently attached and uses system-assigned identity You need to use Python code to update the Synapse Spark Compute 10 use a user-assigned identity.

Solution: Configure the IdentityConfiguration class with the appropriate identity type.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 38

You are using Azure Machine Learning to monitor a trained and deployed model. You implement Event Grid to respond to Azure Machine Learning events.

Model performance has degraded due to model input data changes.

You need to trigger a remediation ML pipeline based on an Azure Machine Learning event.

Which event should you use?

Options:

A.

RunStatusChanged

B.

DatasetDriftDetected

C.

ModelDeployed

D.

RunCompleted

Question 39

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:

Question 40

You manage an Azure Machine learning workspace.

You build a custom model you must log with Mlftow. The custom model includes the following:

• The model is not natively supported by Mlflow.

• The model cannot be serialized in Pickle format.

• The model source code is complex.

• The Python library tor the model must be packaged with the model.

You need to create a custom model flavor to enable logging with ML. flow.

What should you use?

Options:

A.

model loader

B.

custom signatures

C.

model wrapper

D.

artifacts

Question 41

You are profiling mltabte data assets by using Azure Machine Learning studio. You need to detect columns with odd or missing values. Which statistic should you analyze?

Options:

A.

Profile

B.

Std deviation

C.

Error count

D.

Type

Question 42

You manage an Azure Machine Learning workspace. You plan to import data from Azure Data Lake Storage Gen2. You need to build a URI that represents the storage location. Which protocol should you use?

Options:

A.

abfss

B.

https

C.

adl

D.

wasbs

Question 43

You use the Azure Machine Learning SDK to run a training experiment that trains a classification model and calculates its accuracy metric.

The model will be retrained each month as new data is available.

You must register the model for use in a batch inference pipeline.

You need to register the model and ensure that the models created by subsequent retraining experiments are registered only if their accuracy is higher than the currently registered model.

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

NOTE: Each correct selection is worth one point.

Options:

A.

Specify a different name for the model each time you register it.

B.

Register the model with the same name each time regardless of accuracy, and always use the latest

version of the model in the batch inferencing pipeline.

C.

Specify the model framework version when registering the model, and only register subsequent models if this value is higher.

D.

Specify a property named accuracy with the accuracy metric as a value when registering the model, and only register subsequent models if their accuracy is higher than the accuracy property value of the

currently registered model.

E.

Specify a tag named accuracy with the accuracy metric as a value when registering the model, and only register subsequent models if their accuracy is higher than the accuracy tag value of the currently

registered model.

Demo: 43 questions
Total 428 questions