[January-2022]New Braindump2go DP-100 PDF Dumps(Q299-Q307)

QUESTION 299

You use Azure Machine Learning to train a model based on a dataset named dataset1.

You define a dataset monitor and create a dataset named dataset2 that contains new data.

You need to compare dataset1 and dataset2 by using the Azure Machine Learning SDK for Python.

Which method of the DataDriftDetector class should you use?


A.run

B.get

C.backfill

D.update


Answer: C


QUESTION 300

You use an Azure Machine Learning workspace.

You have a trained model that must be deployed as a web service. Users must authenticate by using Azure Active Directory.

What should you do?


A.Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the token_auth_enabled parameter of the target configuration object to true

B.Deploy the model to Azure Container Instances. During deployment, set the auth_enabled parameter of the target configuration object to true

C.Deploy the model to Azure Container Instances. During deployment, set the token_auth_enabled parameter of the target configuration object to true

D.Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the auth.enabled parameter of the target configuration object to true


Answer: A


QUESTION 301

You have a Jupyter Notebook that contains Python code that is used to train a model.

You must create a Python script for the production deployment. The solution must minimize code maintenance.

Which two actions should you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.


A.Refactor the Jupyter Notebook code into functions

B.Save each function to a separate Python file

C.Define a main() function in the Python script

D.Remove all comments and functions from the Python script


Answer: AC


QUESTION 302

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?


A.Azure Machine Learning compute instance

B.Azure Machine Learning compute cluster

C.Azure Kubernetes Service (AKS)-based inference cluster

D.Azure Container Instance (ACI) compute target


Answer: B


QUESTION 303

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 inferencing run.

What should you do?


A.Create a batch inference pipeline

B.Set the compute target for the pipeline to an inference cluster

C.Create a real-time inference pipeline

D.Clone the pipeline


Answer: A


QUESTION 304

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?


A.Implement the download_dashboard_by_upload_id function

B.Implement the create_group_metric_set function

C.Implement the upload_dashboard_dictionary function

D.Upload the training script


Answer: C


QUESTION 305

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?


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

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

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

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


Answer: C


QUESTION 306

Hotspot Question

You are using an Azure Machine Learning workspace. You set up an environment for model testing and an environment for production.

The compute target for testing must minimize cost and deployment efforts. The compute target for production must provide fast response time, autoscaling of the deployed service, and support real-time inferencing.

You need to configure compute targets for model testing and production.

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

NOTE: Each correct selection is worth one point.

Answer:


QUESTION 307

Drag and Drop Question

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.

Answer:



2022 Latest Braindump2go DP-100 PDF and DP-100 VCE Dumps Free Share:

https://drive.google.com/drive/folders/1GRXSnO2A4MYVb3Cfs4F_07l9l9k9_LAD?usp=sharing

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