You create a binary classification model. The model is registered in an Azure Machine Learning workspace. You use the Azure Machine Learning Fairness SDK to assess the model fairness.You develop a training script for the model on a local machine.You need to load the model fairness metrics into Azure Machine Learning studio.What should you do?

Implement the upload_dashboard_dictionary function

Implement the download_dashboard_by_upload_id function

Implement the create_group_metric_set function

Implement the upload_dashboard_dictionary function

You have a dataset that includes confidential data. You use the dataset to train a model.You must use a differential privacy parameter to keep the data of individuals safe and private.You need to reduce the effect of user data on aggregated results.What should you do?

Decrease the value of the epsilon parameter to increase privacy and reduce accuracy

Decrease the value of the epsilon parameter to reduce the amount of noise added to the data

Increase the value of the epsilon parameter to decrease privacy and increase accuracy

Decrease the value of the epsilon parameter to increase privacy and reduce accuracy

Set the value of the epsilon parameter to 1 to ensure maximum privacy

You use the Azure Machine Learning Python SDK to create a batch inference pipeline.You must publish the batch inference pipeline so that business groups in your organization can use the pipeline. Each business group must be able to specify a different location for the data that the pipeline submits to the model for scoring.You need to publish the pipeline.What should you do?

Define a OutputFileDatasetConfig object for the pipeline and use the object to specify the business group-specific input dataset for each pipeline run.

Create multiple endpoints for the published pipeline service and have each business group submit jobs to its own endpoint.

Define a PipelineParameter object for the pipeline and use it to specify the business group-specific input dataset for each pipeline run.

Define a OutputFileDatasetConfig object for the pipeline and use the object to specify the business group-specific input dataset for each pipeline run.

Have each business group run the pipeline on local compute and use a local file for the input data.

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?

Register the model with the workspace.

Deploy the model to a managed online endpoint.

Register the model with the workspace.

Convert the model from the MLflow format to a custom format.

You are developing a machine learning model.You must inference the machine learning model for testing.You need to use a minimal cost compute targetWhich two compute targets should you use? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point

Azure Machine Learning Kubernetes

You are creating a compute target to train a machine learning experiment.The compute target must support automated machine learning, machine learning pipelines, and Azure Machine Learning designer training.You need to configure the compute targetWhich option should you use?

Azure Machine Learning compute cluster

You manage an Azure Machine Learning workspace by using the Azure CLI ml extension v2. You need to define a YAML schema to create a compute cluster. Which schema should you use?

https://azuremlschemas.azureedge.net/latest/amlCompute.schemajson

https://azuremlschemas.azureedge.net/latest/computdnstarKeichema.json

https://azuremlschemas.azureedge.net/latest/amlCompute.schemajson

https://azuremlschemas.azureedge.net/latest/vmCompute.schema.json

https://azuremlschemas.azureedge.net/latest/kubernetesCompute.schema.json

You create a training pipeline by using the Azure Machine Learning designer. You need to load data into a machine learning pipeline by using the Import Data component. Which two data sources could you use? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point

Azure Blob storage container through a registered datastore

Microsoft DP-100 Practice Test 7 - Free Online Exam Prep & Questions

You use the Azure Machine Learning designer to create and run a training pipeline.

The pipeline must be run every night to inference predictions from a large volume of files. The folder where the files will be stored is defined as a dataset.

You need to publish the pipeline as a REST service that can be used for the nightly influencing run.

What should you do?

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Microsoft DP-100 Practice Test 7

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Microsoft DP-100 Practice Tests

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