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DP-100 Exam Dumps - Microsoft Azure Questions and Answers

Question # 34

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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Question # 35

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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Question # 36

You manage an Azure Machine Learning workspace.

You experiment with an MLflow model that trains interactively by using a notebook in the workspace. You need to log dictionary type artifacts of the experiments in Azure Machine Learning by using MLflow. Which syntax should you use?

Options:

A.

mlflow.log_artifact(my_dict)

B.

mlflow.log_metric("my_metric", my_dict)

C.

mlflow.log_artifacts(my_dict>

D.

mlflow.log metrics(my diet)

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Question # 37

You create an Azure Machine Learning workspace

You are developing a Python SDK v2 notebook to perform custom model training in the workspace. The notebook code imports all required packages.

You need to complete the Python SDK v2 code to include a training script. environment, and compute information.

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

NOTE: Each correct selection is worth one point

Options:

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Question # 38

You plan to use automated machine learning by using Azure Machine Learning Python SDK v2 to train a regression model. You have data that has features with missing values, and categorical features with few distinct values.

You need to control whether automated machine learning automatically imputes missing values and encode categorical features as part of the training task. Which enemy of the autumn package should you use?

Options:

A.

ForecastHorizonMode

B.

RegressionPrimaryMetrics

C.

RegressionModels

D.

FeaturizationMode

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Question # 39

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?

Options:

A.

Yes

B.

No

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Question # 40

You ate designing a training job in an Azure Machine Learning workspace by using Automated ML During training, the compute resource must scale up to handle larger datasets. You need to select the compute resource that has a multi-node cluster that automatically scales Which Azure Machine Learning compute target should you use?

Options:

A.

Compute instance

B.

Endpoints

C.

Serverless compute

D.

Kubernetes cluster

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Question # 41

You use Azure Machine Learning to train a model. You must use Bayesian sampling to tune hyperparameters. You need to select a ieaming_rate parameter distribution.

Which two distributions can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

Options:

A.

Uniform

B.

LogUniform

C.

Normal

D.

Choice

E.

QNormal

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Question # 42

You manage an Azure Al Foundry project.

You develop a Prompt flow that includes a large language model (LLM) node and an upstream node with a single output. You need to link the LLM node input with the output of the upstream node by using a YAML flow configuration. Which flow configuration should you use?

Options:

A.

$(upstream_node_name.output)

B.

<#upstream_node_nameoutput#>

C.

(% upstream node_name,output%}

D.

{{upstream.node.nameoutput})

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Question # 43

You are analyzing a raw dataset that requires cleaning.

You must perform transformations and manipulations by using Azure Machine Learning Studio.

You need to identify the correct modules to perform the transformations.

Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module 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.

Options:

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Exam Code: DP-100
Exam Name: Designing and Implementing a Data Science Solution on Azure
Last Update: Aug 16, 2025
Questions: 506
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