DP-100 Designing and Implementing a Data Science Solution on Azure Questions and Answers

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.

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.

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.

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

Which normalization type should you use?

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?

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

What should you do?

You use the Azure Machine Learning designer to create and run a training pipeline. You then create a real-time inference pipeline.

You must deploy the real-time inference pipeline as a web service.

What must you do before you deploy the real-time inference pipeline?

You must use in Azure Data Science Virtual Machine (DSVM) as a compute target.

You need to attach an existing DSVM to the workspace by using the Azure Machine Learning SDK for Python.

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

NOTE: Each correct selection is worth one point.

You create a machine learning model by using the Azure Machine Learning designer. You publish the model as a real-time service on an Azure Kubernetes Service (AKS) inference compute cluster. You make no changes to the deployed endpoint configuration.

You need to provide application developers with the information they need to consume the endpoint.

Which two values should you provide to application developers? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

You create an Azure Machine Learning model to include model files and a scorning script. You must deploy the model. The deployment solution must meet the following requirements:

• Provide near real-time inferencing.

• Enable endpoint and deployment level cost estimates.

• Support logging to Azure Log Analytics.

You need to configure the deployment solution.

What should you configure? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You create an Azure Machine Learning workspace. You train a classification model by using automated machine learning (automated ML) in Azure Machine Learning studio. The training data contains multiple classes that have significantly different numbers of samples.

You must use a metric type to avoid labeling negative samples as positive and an averaging method that will minimize the class imbalance.

You need to configure the metric type and the averaging method.

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

NOTE: Each correct selection is worth one point.

You use the following code to define the steps for a pipeline:

from azureml.core import Workspace, Experiment, Run

from azureml.pipeline.core import Pipeline

from azureml.pipeline.steps import PythonScriptStep

ws = Workspace.from_config()

. . .

step1 = PythonScriptStep(name="step1", ...)

step2 = PythonScriptsStep(name="step2", ...)

pipeline_steps = [step1, step2]

You need to add code to run the steps.

Which two code segments can you use to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

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: Accuracy, Precision, Recall, F1 score and AUC.

Does the solution meet the goal?

You create an Azure Machine Learning workspace and install the MLflow library.

You need to tog different types of data by using the MLflow library.

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

NOTE: Each correct selection is worth one point.

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.

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.

You create an Azure Machine Learning dataset containing automobile price data. The dataset includes 10.000 rows and 10 columns. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script component and custom code.

The code must combine three columns to create a new column.

You need to configure the code function.

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

NOTE: Each correct selection is worth one point.

: 212

You register a model that you plan to use in a batch inference pipeline.

The batch inference pipeline must use a ParallelRunStep step to process files in a file dataset. The script has the ParallelRunStep step runs must process six input files each time the inferencing function is called.

You need to configure the pipeline.

Which configuration setting should you specify in the ParallelRunConfig object for the PrallelRunStep step?

You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).

The remaining 1,000 rows represent class 1 (10 percent).

The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.

You need to configure the module.

Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

You train and register a model in your Azure Machine Learning workspace.

You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data.

You need to create the inferencing script for the ParallelRunStep pipeline step.

Which two functions should you include? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

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 and set the value of its auth.mode parameter to aml.token. Deploy the model to the online endpoint.

Does the solution meet the goal?

You create a classification model with a dataset that contains 100 samples with Class A and 10,000 samples with Class B

The variation of Class B is very high.

You need to resolve imbalances.

Which method should you use?

You train and register a machine learning model. You create a batch inference pipeline that uses the model to generate predictions from multiple data files.

You must publish the batch inference pipeline as a service that can be scheduled to run every night.

You need to select an appropriate compute target for the inference service.

Which compute target should you use?

You have an Azure Machine Learning workspace. You are running an experiment on your local computer.

You need to use MLflow Tracking to store metrics and artifacts from your local experiment runs in the workspace.

In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

You are working on a classification task. You have a dataset indicating whether a student would like to play soccer and associated attributes. The dataset includes the following columns:

You need to classify variables by type.

Which variable should you add to each category? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You are developing a machine learning model by using Azure Machine Learning. You are using multiple text files in tabular format for model data. You have the following requirements:

• You must use AutoML jobs to train the model.

• You must use data from specified columns.

• The data concept must support lazy evaluation.

You need to load data into a Pandas dataframe.

Which data concept should you use?

You create an Azure Machine Learning workspace. You train an MLflow-formatted regression model by using tabular structured data.

You must use a Responsible Al dashboard to assess the model.

You need to use the Azure Machine Learning studio Ul to generate the Responsible A dashboard.

What should you do first?

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 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 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.

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.

You create an Azure Machine Learning dataset. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script component and custom code.

You must upload the script and associated libraries as a script bundle.

You need to configure the Execute Python Script component.

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

NOTE Each correct selection is worth one point.

: 216

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 train a classification model by using a logistic regression algorithm.

You must be able to explain the model’s predictions by calculating the importance of each feature, both as an overall global relative importance value and as a measure of local importance for a specific set of predictions.

You need to create an explainer that you can use to retrieve the required global and local feature importance values.

Solution: Create a TabularExplainer.

Does the solution meet the goal?

You create an Azure Machine Learning workspace.

You need to detect data drift between a baseline dataset and a subsequent target dataset by using the DataDriftDetector class.

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.

You create a binary classification model. You use the Fairlearn package to assess model fairness. You must eliminate the need to retrain the model. You need to implement the Fair learn package. Which algorithm should you use?

You are conducting feature engineering to prepuce data for further analysis.

The data includes seasonal patterns on inventory requirements.

You need to select the appropriate method to conduct feature engineering on the data.

Which method should you use?

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.

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: Relative Squared Error, Coefficient of Determination, Accuracy, Precision, Recall, F1 score, and AUC.

Does the solution meet the goal?

You need to select a feature extraction method.

Which method should you use?

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.

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.

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.

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.

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.

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.

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.

You need to select a feature extraction method.

Which method should you use?

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.

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.

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.

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

Which environment should you use?