Online DP-100 Dumps Help You Understand Questions Well

1. You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts. Data processed by the first step is passed to the second step.

You must update the content of the downstream data source of pipeline 1 and run the pipeline again.

You need to ensure the new run of pipeline 1 fully processes the updated content.

Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps.

Does the solution meet the goal'

2. You are analyzing a dataset by using Azure Machine Learning Studio.

YOU need to generate a statistical summary that contains the p value and the unique value count for each feature column.

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

3. You manage an Azure Machine Learning workspace. The Pylhon scrip! named scriptpy reads an argument named training_data. The trainlng.data argument specifies the path to the training data in a file named datasetl.csv. You plan to run the scriptpy Python script as a command job that trains a machine learning model. You need to provide the command to pass the path for the datasct as a parameter value when you submit the script as a training job.

Solution: python script.py Ctraining_data dataset1, csv

Does the solution meet the goal?

4. You manage an Azure Machine learning workspace. The workspace includes an Azure Machine Learning kubernetes compute target configured as an Azure Kubemetes Service (AKS) cluster named AKS1 AKS1 is configured to enable the targeting of different nodes to train workloads.

You must run a command job on AK51 by using the Azure ML Python SDK v2? The command job must select different types of compute nodes. The compare node types must be specified by using a command parameter.

You need to configure the command parameter.

Which parameter should you use?

5. You are a data scientist working for a bank and have used Azure ML to train and register a machine learning model that predicts whether a customer is likely to repay a loan.

You want to understand how your model is making selections and must be sure that the model does not violate government regulations such as denying loans based on where an applicant lives.

You need to determine the extent to which each feature in the customer data is influencing predictions.

What should you do?

6. 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 have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.

You must run the script as an Azure ML experiment on a compute cluster named aml-compute.

You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.

Solution: Run the following code:





Does the solution meet the goal?

7. HOTSPOT

You are retrieving data from a large datastore by using Azure Machine Learning Studio.

You must create a subset of the data for testing purposes using a random sampling seed based on the system clock.

You add the Partition and Sample module to your experiment.

You need to select the properties for the module.

Which values should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

8. You manage an Azure Machine Learning workspace.

You must provide explanations for the behavior of the models with feature importance measures.

You need to configure a Responsible Al dashboard in Azure Machine Learning.

Which dashboard component should you configure?

9. You manage an Azure Machine Learning workspace. The Pylhon scrip! named scriptpy reads an argument named training_data. The trainlng.data argument specifies the path to the training data in a file named datasetl.csv. You plan to run the scriptpy Python script as a command job that trains a machine learning model. You need to provide the command to pass the path for the datasct as a parameter value when you submit the script as a training job.

Solution: python script.py Ctraining_data ${{inputs,training_data}}

Does the solution meet the goal?

10. You train and publish a machine teaming model.

You need to run a pipeline that retrains the model based on a trigger from an external system.

What should you configure?

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

Which normalization type should you use?

12. HOTSPOT

You have an Azure blob container that contains a set of TSV files. The Azure blob container is registered as a datastore for an Azure Machine Learning service workspace. Each TSV file uses the same data schema.

You plan to aggregate data for all of the TSV files together and then register the aggregated data as a dataset in an Azure Machine Learning workspace by using the Azure Machine Learning SDK for Python.

You run the following code.





For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

13. HOTSPOT

You perform hyper parameter tuning with Azure Machine Learning.

You create the following Python code:





For each of the following statements, select Yes if the statement is true. Otherwise, select No.

14. You use Azure Machine Learning designer to create a real-time service endpoint. You have a single Azure Machine Learning service compute resource. You train the model and prepare the real-time pipeline for deployment You need to publish the inference pipeline as a web service.

Which compute type should you use?

15. HOTSPOT

You are performing feature scaling by using the scikit-learn Python library for x.1 x2, and x3 features.

Original and scaled data is shown in the following image.





Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

16. HOTSPOT

You use Azure Machine Learning to implement hyperparameter tuning with a Bandit early termination policy.

The policy uses a slack_factor set to 01. an evaluation interval set to 1, and an evaluation delay set to b.

You need to evaluate the outcome of the early termination policy.

What should you evaluate? To answer, select the appropriate options m the answer area. NOTE: Each correct selection is worth one point.

17. 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 create an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:

• /data/2018/Q1.csv

• /data/2018/Q2.csv

• /data/2018/Q3.csv

• /data/2018/Q4.csv

• /data/2019/Q1.csv

All files store data in the following format:

id,f1,f2i

1,1.2,0

2,1,1,

1 3,2.1,0

You run the following code:





You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:





Solution: Run the following code:





Does the solution meet the goal?

18. HOTSPOT

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.

19. 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?

20. You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size.

You have the following requirements:

✑ Models must be built using Caffe2 or Chainer frameworks.

✑ Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments.

✑ Personal devices must support updating machine learning pipelines when connected to a network.

You need to select a data science environment.

Which environment should you use?

21. You manage an Azure Machine Learning workspace. You design a training job that is configured with a serverless compute. The serverless compute must have a specific instance type and count

You need to configure the serverless compute by using Azure Machine Learning Python SDK v2.

What should you do?

22. You manage an Azure Machine Learning workspace named workspaces

You K v2 code to attach an Azure Synapse Spark pool as a compute target in workspaces. The code must invoke the constructor of the SynapseSparkCompute class.

You need to invoke the constructor.

What should you use?

23. 2.1.0

You run the following code:





You need to create a dataset named training_data and load the data from all files into a single data

frame by using the following code:





Solution: Run the following code:





Does the solution meet the goal?

24. You manage an Azure Al Foundry project. You build a multi-turn chatbot application.

You plan to filter your traces to identity issues while observing how the application is responding.

The solution must not use an external knowledge base. You need to select an evaluation metric.

Which built-in evaluator should you use?

25. You have an Azure Machine Learning workspace. You are connecting an Azure Data Lake Storage Gen2 account to the workspace as a data store. You need to authorize access from the workspace to the Azure Data Lake Storage Gen2 account.

What should you use?

26. You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data.

You need to select a data cleaning method.

Which method should you use?

27. 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.

28. 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 Machine Learning Studio.

One class has a much smaller number of observations than tin- other classes in the training set.

You need to select an appropriate data sampling strategy to compensate for the class imbalance.

Solution: You use the Principal Components Analysis (PCA) sampling mode.

Does the solution meet the goal?

29. You have the following Azure subscriptions and Azure Machine Learning service workspaces:





You need to obtain a reference to the ml-project workspace.

Solution: Run the following Python code:





Does the solution meet the goal?

30. You are creating a classification model for a banking company to identify possible instances of credit card fraud. You plan to create the model in Azure Machine Learning by using automated machine learning.

The training dataset that you are using is highly unbalanced.

You need to evaluate the classification model.

Which primary metric should you use?

31. HOTSPOT

You train a machine learning model by using Aunt Machine Learning.

You use the following training script m Python to log an accuracy value.





You must use a Python script to define a sweep job.

You need to provide the primary metric and goal you want hyper parameter tuning to optimize.

How should you complete the Python script? To answer select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

32. HOTSPOT

You develop a chat flow in an Azure Al Foundry project

You plan to include a Jinja language-based prompt template in the How

You need to complete the provided template to display a list of inputs and outputs included in the flow.

How should you complete the provided template? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

33. You are a data scientist creating a linear regression model.

You need to determine how closely the data fits the regression line.

Which metric should you review?

34. 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?

35. HOTSPOT

You are using a decision tree algorithm. You have trained a model that generalizes well at a tree depth equal to 10.

You need to select the bias and variance properties of the model with varying tree depth values.

Which properties should you select for each tree depth? To answer, select the appropriate options in the answer area.

36. You use Azure Machine Learning to tram a model.

You must use Baylean sampling to Tune hyperparaters.

You need to select a learning_rate parameter distribution.

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

37. You create a Python script that runs a training experiment in Azure Machine Learning. The script uses the Azure Machine Learning SDK for Python.

You must add a statement that retrieves the names of the logs and outputs generated by the script.

You need to reference a Python class object from the SDK for the statement.

Which class object should you use?

38. HOTSPOT

You monitor an Azure Machine Learning classification training experiment named train-classification on Azure Notebooks.

You must store a table named table as an artifact in Azure Machine Learning Studio during model training.

You need to collect and list the metrics by using MLfow.

How should you complete the code segment? To answer, select the appropriate option in the answer area. NOTE: Each correct selection is worth on* point.

39. DRAG DROP

You create a multi-class image classification deep learning experiment by using the PyTorch framework. You plan to run the experiment on an Azure Compute cluster that has nodes with GPU’s.

You need to define an Azure Machine Learning service pipeline to perform the monthly retraining of the image classification model. The pipeline must run with minimal cost and minimize the time required to train the model.

Which three pipeline steps should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

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

What should you do?

41. HOTSPOT

You are using the Azure Machine Learning Service to automate hyperparameter exploration of your neural network classification model.

You must define the hyperparameter space to automatically tune hyperparameters using random sampling according to following requirements:

The learning rate must be selected from a normal distribution with a mean value of 10 and a standard deviation of 3.

Batch size must be 16, 32 and 64.

Keep probability must be a value selected from a uniform distribution between the range of 0.05 and 0.1.

You need to use the param_sampling method of the Python API for the Azure Machine Learning Service.

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.

42. HOTSPOT

You have an Azure Machine learning workspace. The workspace contains a dataset with data in a tabular form.

You plan to use the Azure Machine Learning SDK for Python vl to create a control script that will load the dataset into a pandas dataframe in preparation for model training. The script will accept a parameter designating the dataset

You need to complete the script.

How should you complete the script? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

43. You manage an Azure Machine Learning workspace. The development environment for 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 to use a user-assigned identity.

Solution: Initialize the DefaultAzureCredential class.

Does the solution meet the goal?

44. You have an Azure Machine Learning workspace named Workspace 1 Workspace! has a registered Mlflow model named model 1 with PyFunc flavor

You plan to deploy model1 to an online endpoint named endpoint1 without egress connectivity by using Azure Machine learning Python SDK vl

You have the following code:





You need to add a parameter to the ManagedOnlineDeployment object to ensure the model deploys successfully

Solution: Add the environment parameter.

Does the solution meet the goal?

45. 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 using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model.

You configure a HyperDriveConfig for the experiment by running the following code:





You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted.

You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.

Solution: Run the following code:





Does the solution meet the goal?

46. 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 and register a machine learning model.

You plan to deploy the model as a real-time web service. Applications must use key-based authentication to use the model.

You need to deploy the web service.

Solution:

Create an AciWebservice instance.

Set the value of the ssl_enabled property to True.

Deploy the model to the service.

Does the solution meet the goal?

47. DRAG DROP

You have an Azure Machine Learning workspace that contains a training cluster and an inference cluster.

You plan to create a classification model by using the Azure Machine Learning designer.

You need to ensure that client applications can submit data as HTTP requests and receive predictions as responses.

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.

48. 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 using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model.

You configure a HyperDriveConfig for the experiment by running the following code:





You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted.

You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.

Solution: Run the following code:





Does the solution meet the goal?

49. HOTSPOT

You arc I mating a deep learning model to identify cats and dogs. You have 25,000 color images.

You must meet the following requirements:

• Reduce the number of training epochs.

• Reduce the size of the neural network.

• Reduce over-fitting of the neural network.

You need to select the image modification values.

Which value should you use? To answer, select the appropriate Options in the answer area. NOTE: Each correct selection is worth one point.

50. You have a dataset that is stored m an Azure Machine Learning workspace.

You must perform a data analysis for differentiate privacy by using the SmartNoise SDK.

You need to measure the distribution of reports for repeated queries to ensure that they are balanced

Which type of test should you perform?

51. You retrain an existing model.

You need to register the new version of a model while keeping the current version of the model in the registry.

What should you do?

52. HOTSPOT

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.

53. HOTSPOT

You are running a training experiment on remote compute in Azure Machine Learning.

The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages.

You must use MLflow as the logging package for tracking metrics generated in the experiment.

You need to complete the script for the experiment.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

54. HOTSPOT

You manage an Azure Al Foundry project.

You plan 10 build a RAG solution.

The solution must include two models:

• One for text output, named Model1. This model must resemble human language and read naturally.

• One for creating embeddings, named Model2. This model must maximize the retrieval of relevant results (high recall)

You need to compare different models by using benchmarking metrics to select the appropriate models for Model1 and Model?

55. DRAG DROP

You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.

The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must identify the feature that has the most influence on the predictions of the model for the second highest scoring algorithm. You must minimize the effort and time to identify the feature.

You need to complete the identification.

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.

56. HOTSPOT

You use an Azure Machine Learning workspace.

You create the following Python code:





For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

57. 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 using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model.

You configure a HyperDriveConfig for the experiment by running the following code:





variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted. You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.

Solution: Run the following code:





Does the solution meet the goal?

58. 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 use Azure Machine Learning designer to load the following datasets into an experiment:





You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Join Data module.

Does the solution meet the goal?

59. DRAG DROP

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

The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images, and retrain the model.

You need to use the Azure Machine Learning SDK to configure the schedule for the pipeline.

Which four 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.

60. HOTSPOT

You plan to use Hyperdrive to optimize the hyperparameters selected when training a model.

You create the following code to define options for the hyperparameter experiment





For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE:

Each correct selection is worth one point.

61. DRAG DROP

You manage an Azure Machine Learning workspace named workspace1by using the Python SDK v2.

You must register datastores in workspace 1 for Azure Blot storage and Azure Fetes storage to meet the following requirements.

* Azure Active Directory (Azure AD) authentication must be used for access to storage when possible.

* Credentials and secrets steed in workspace1 must be valid lot a specified time period when accessing Azure Files storage.

You need to configure a security access method used to register the Azure Blob and azure files storage in workspace1.

Which security access method should you configure? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

62. DRAG DROP

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

You need to ensure that you can use MLflow Tracking with Azure Machine Learning Python SDK v2 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.

63. DRAG DROP

You need to implement source control for scripts in an Azure Machine Learning workspace. You use a

terminal window in the Azure Machine Learning Notebook tab You must authenticate your Git account with SSH. You need to generate a new SSH key.

Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them m the correct order.

64. HOTSPOT

You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset.

The C-Support Vector classification using Python code shown below:





You need to evaluate the C-Support Vector classification code.

Which evaluation statement should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

65. HOTSPOT

You are using hyperparameter tuning in Azure Machine Learning Python SDK v2 to train a model.

You configure the hyperparameter tuning experiment by running the following code:





For each of the following statements select Yes if the statement is true. Otherwise, select No. NOTE: Fach correct selection is worth one paint.

66. HOTSPOT

You manage an Azure Machine Learning workspace. You configure an automated machine learning regression training job by using the Azure Machine Learning Python SDK v2.

You configure the regression job by using the following script:





For each of the following statements, select Yes if the statement is true. Otherwise, select No.

67. You are implementing a machine learning model to predict stock prices.

The model uses a PostgreSQL database and requires GPU processing.

You need to create a virtual machine that is pre-configured with the required tools.

What should you do?

68. HOTSPOT

You are tuning a hyperparameter for an algorithm. The following table shows a data set with different hyperparameter, training error, and validation errors.





Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.

69. You use differential privacy to ensure your reports are private. The calculated value of the epsilon for your data is 1.8. You need to modify your data to ensure your reports are private.

Which epsilon value should you accept for your data?

70. You use the following Python code in a notebook to deploy a model as a web service:





The deployment fails.

You need to use the Python SDK in the notebook to determine the events that occurred during service deployment an initialization.

Which code segment should you use?

71. HOTSPOT

You train a classification model by using a decision tree algorithm.

You create an estimator by running the following Python code. The variable feature_names is a list of all feature names, and class_names is a list of all class names.

from interpret.ext.blackbox import TabularExplainer





You need to explain the predictions made by the model for all classes by determining the importance of all features.

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

72. HOTSPOT

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.

73. You have an Azure Machine Learning workspace. You plan to tune model hyperparameters by using a sweep job.

You need to find a sampling method that supports early termination of low-performance jobs and continuous hyperpara meters.

Solution: Use the Bayesian sampling method over the hyperparameter space.

Does the solution meet the goal?

74. HOTSPOT

You have a feature set containing the following numerical features: X, Y, and Z.

The Poisson correlation coefficient (r-value) of X, Y, and Z features is shown in the following image:





Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

75. You manage an Azure Machine Learning workspace. The Pylhon scrip! named scriptpy reads an argument named training_data. The trainlng.data argument specifies the path to the training data in a file named datasetl.csv. You plan to run the scriptpy Python script as a command job that trains a machine learning model. You need to provide the command to pass the path for the datasct as a parameter value when you submit the script as a training job.

Solution: python train.py --training_data training_data

Does the solution meet the goal?

76. You deploy a model as an Azure Machine Learning real-time web service using the following code.





The deployment fails.

You need to troubleshoot the deployment failure by determining the actions that were performed during deployment and identifying the specific action that failed.

Which code segment should you run?

77. HOTSPOT

You manage an Azure Machine Learning workspace by using the Python SDK v2.

You must create a compute cluster in the workspace. The compute cluster must run workloads and properly handle interruptions. You start by calculating the maximum amount of compute resources required by the workloads and size the cluster to match the calculations.

The cluster definition includes the following properties and values:

• name="mlcluster1’’

• size="STANDARD.DS3.v2"

• min_instances=1

• maxjnstances=4

• tier="dedicated"

The cost of the compute resources must be minimized when a workload is active Of idle. Cluster property changes must not affect the maximum amount of compute resources available to the workloads run on the cluster.

You need to modify the cluster properties to minimize the cost of compute resources.

Which properties should you modify? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

78. You need to select a pre built development environment for a series of data science experiments. You must use the R language for the experiments.

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

79. You are creating a machine learning model. You have a dataset that contains null rows.

You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset.

Which parameter should you use?

80. You create an Azure Machine Learning workspace. The workspace contains a dataset named sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline that will prepare data in the dataset and then train and register a model based on the prepared data.

The first stage of the pipeline contains the following code:





You need to identify the location containing the output of the first stage of the script that you can use as input for the second stage.

Which storage location should you use?

81. HOTSPOT

You are a lead data scientist for a project that tracks the health and migration of birds. You create a multi-image classification deep learning model that uses a set of labeled bird photos collected by experts. You plan to use the model to develop a cross-platform mobile app that predicts the species of bird captured by app users.

You must test and deploy the trained model as a web service.

The deployed model must meet the following requirements:

✑ An authenticated connection must not be required for testing.

✑ The deployed model must perform with low latency during inferencing.

✑ The REST endpoints must be scalable and should have a capacity to handle large number of requests when multiple end users are using the mobile application.

You need to verify that the web service returns predictions in the expected JSON format when a valid REST request is submitted.

Which compute resources should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

82. 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 using Azure Machine Learning Studio to perform feature engineering on a dataset.

You need to normalize values to produce a feature column grouped into bins.

Solution: Apply an Entropy Minimum Description Length (MDL) binning mode.

Does the solution meet the goal?

83. HOTSPOT

You manage are Azure Machine Learning workspace by using the Python SDK v2.

You must create an automated machine learning job to generate a classification model by using data files stored in Parquet format. You must configure an auto scaling compute target and a data asset for the job.

You need to configure the resources for the job.

Which resource configuration should you use? to answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

84. You are developing a machine learning model.

You must inference the machine learning model for testing.

You need to use a minimal cost compute target

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

85. You have fine-tuned an Azure OpenAI Service model by using the Azure Ai Foundry portal. The fine-tuned model is overfitting.

You plan to correct overfitting by fine-tuning the model again

You need to modify the default value of a fine-tuning task parameter to minimize the possibility of overfitting.

Which modification should you apply?

86. HOTSPOT

You are the owner of an Azure Machine Learning workspace.

You must prevent the creation or deletion of compute resources by using a custom role. You must allow all other operations inside the workspace.

You need to configure the custom role.

How should you complete the configuration? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

87. 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 Machine Learning Studio.

One class has a much smaller number of observations than the other classes in the training set.

You need to select an appropriate data sampling strategy to compensate for the class imbalance.

Solution: You use the Scale and Reduce sampling mode.

Does the solution meet the goal?

88. HOTSPOT

You create a new Azure Machine Learning workspace with a compute cluster.

You need to create the compute cluster asynchronously by using the Azure Machine Learning Python SDK v2.

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

89. 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 PFIExplainer.

Does the solution meet the goal?

90. you create an Azure Machine learning workspace named workspace1. The workspace contains a Python SOK v2 notebook mat uses Mallow to correct model coaxing men’s anal arracks from your local computer.

Vou must reuse the notebook to run on Azure Machine I earning compute instance m workspace.

You need to comminute to log training and artifacts from your data science code.

What should you do?

91. You plan to provision an Azure Machine Learning Basic edition workspace for a data science project.

You need to identify the tasks you will be able to perform in the workspace.

Which three tasks will you be able to perform? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

92. HOTSPOT

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.

93. You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure Machine Learning SDK.

You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute.

You define a DataReference object by running the following code:





You need to load the training data.

Which code segment should you use?

A)





B)





C)





D)





E)

94. HOTSPOT

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.

95. DRAG DROP

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.

96. HOTSPOT

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.

97. 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?

98. DRAG DROP

You are creating a machine learning model that can predict the species of a penguin from its measurements. You have a file that contains measurements for free species of penguin in comma delimited format.

The model must be optimized for area under the received operating characteristic curve performance metric averaged for each class.

You need to use the Automated Machine Learning user interface in Azure Machine Learning studio to run an experiment and find the best performing model.

Which five 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 collect order.

99. HOTSPOT

You create an Azure Data Lake Storage Gen2 stowage account named storage1 containing a file system named fsi and a folder named folder1.

The contents of folder1 must be accessible from jobs on compute targets in the Azure Machine Learning workspace.

You need to construct a URl to reference folder1.

How should you construct the URI? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

100. You create an Azure Machine Learning workspace.

You must configure an event handler to send an email notification when data drift is detected in the workspace datasets. You must minimize development efforts.

You need to configure an Azure service to send the notification.

Which Azure service should you use?

101. You create an Azure Machine Learning workspace named ML-workspace. You also create an Azure Databricks workspace named DB-workspace. DB-workspace contains a cluster named DB-cluster.

You must use DB-cluster to run experiments from notebooks that you import into DB-workspace.

You need to use ML-workspace to track MLflow metrics and artifacts generated by experiments running on DB-cluster. The solution must minimize the need for custom code.

What should you do?

102. HOTSPOT

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 first 1.000 rows represent class 1 (10 percent).

The training set is unbalanced between two Classes. You must increase the number of training examples for class 1 to 4,000 by using 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.

103. 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

104. You create a script that trains a convolutional neural network model over multiple epochs and logs the validation loss after each epoch. The script includes arguments for batch size and learning rate.

You identify a set of batch size and learning rate values that you want to try.

You need to use Azure Machine Learning to find the combination of batch size and learning rate that results in the model with the lowest validation loss.

What should you do?

105. DRAG DROP

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

The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images and retrain the model.

You need to use the Azure Machine Learning Python SEX v2 to configure the schedule for the pipeline. The schedule should be defined by using the frequency and interval properties with frequency set to month' and interval set to "1:

Which three classes should you instantiate in sequence"' To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

106. 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?

107. You use Azure Machine Learning Designer to load the following datasets into an experiment:

Dataset1





Dataset2





You use Azure Machine Learning Designer to load the following datasets into an experiment:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Join Data component.

Does the solution meet the goal?

108. HOTSPOT

You load data from a notebook in an Azure Machine Learning workspace into a pandas dataframe named df. The data contains 10.000 patient records. Each record includes the Age property for the corresponding patient.

You must identify the mean age value from the differentially private data generated by SmartNoise SDK.

You need to complete the Python code that will generate the mean age value from the differentially private data.

Which code segments should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

109. 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?

110. You have an Azure Machine Learning workspace.

You plan to run a job to tram a model as an MLflow model output.

You need to specify the output mode of the MLflow model.

Which three modes can you specify? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

111. You are building a regression model tot estimating the number of calls during an event.

You need to determine whether the feature values achieve the conditions to build a Poisson regression model.

Which two conditions must the feature set contain? I ach correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

112. DRAG DROP

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.

113. HOTSPOT

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

You need to define the method signature for the Execute Python Script component and return value type.

What should you define? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

114. You need to select a feature extraction method.

Which method should you use?

115. DRAG DROP

You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.

The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must preview the data profile in Azure Machine Learning studio once the dataset is created.

You need to train the model.

Which four 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.

116. You are creating a machine learning model.

You need to identify outliers in the data.

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

117. You create a batch inference pipeline by using the Azure ML SDK.

You configure the pipeline parameters by executing the following code:





You need to obtain the output from the pipeline execution.

Where will you find the output?

118. You are building a binary classification model by using a supplied training set.

The training set is imbalanced between two classes.

You need to resolve the data imbalance.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution NOTE: Each correct selection is worth one point.

119. 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.

An IT department creates the following Azure resource groups and resources:





The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace. You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.

You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.

Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace. Run the training script as an experiment on the aks-cluster compute target.

Does the solution meet the goal?

120. HOTSPOT

You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.

The following image displays the results dataset output:





Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image. NOTE: Each correct selection is worth one point.

121. HOTSPOT

space and set up a development environment. You plan to train a deep neural network (DNN) by using the Tensorflow framework and by using estimators to submit training scripts.

You must optimize computation speed for training runs.

You need to choose the appropriate estimator to use as well as the appropriate training compute target configuration.

Which values should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

122. HOTSPOT

You have a Python data frame named salesData in the following format:





The data frame must be unpivoted to a long data format as follows:





You need to use the pandas.melt() function in Python to perform the transformation.

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.

123. You use Azure Machine Learning to train a model.

You must use a sampling method for tuning hyperparameters. The sampling method must pick samples based on how the model performed with previous samples.

You need to select a sampling method.

Which sampling method should you use?

124. You are moving a large dataset from Azure Machine Learning Studio to a Weka environment.

You need to format the data for the Weka environment.

Which module should you use?

125. You are building a recurrent neural network to perform a binary classification. You review the training loss, validation loss, training accuracy, and validation accuracy for each training epoch.

You need to analyze model performance.

Which observation indicates that the classification model is over fitted?

126. You run Azure Machine Learning training experiments. The training scripts directory contains 100 files that includes a file named. amlignore. The directory also contains subdirectories named. /outputs and./logs.

There are 20 files in the training scripts directory that must be excluded from the snapshot to the compute targets. You create a file named. gift ignore in the root of the directory. You add the names of the 20 files to the. gift ignore file. These 20 files continue to be copied to the compute targets.

You need to exclude the 20 files.

What should you do?

127. You are solving a classification task.

The dataset is imbalanced.

You need to select an Azure Machine Learning Studio module to improve the classification accuracy.

Which module should you use?

128. 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?

129. You must store data in Azure Blob Storage to support Azure Machine Learning.

You need to transfer the data into Azure Blob Storage.

What are three possible ways to achieve the goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

130. You create a datastore named training_data that references a blob container in an Azure Storage account. The blob container contains a folder named csv_files in which multiple comma-separated values (CSV) files are stored.

You have a script named train.py in a local folder named ./script that you plan to run as an experiment using an estimator.

The script includes the following code to read data from the csv_files folder:





You have the following script.





You need to configure the estimator for the experiment so that the script can read the data from a data reference named data_ref that references the csv_files folder in the training_data datastore.

Which code should you use to configure the estimator?

A)





B)





C)





D)





E)

131. HOTSPOT

You manage an Azure Machine Learning workspace named Workspace1 and an Azure Blob Storage accessed by using the URL https://storage1.blob.core.wmdows.net/data1.

You plan to create an Azure Blob datastore in Workspace1. The datastore must target the Blob Storage by using Azure Machine Learning Python SDK v2. Access authorization to the datastore must be limited to a specific amount of time.

You need to select the parameters of the Azure Blob Datastore class that will point to the target datastore and authorize access to it.

Which parameters should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

132. You use Azure Machine Learning Studio to build a machine learning experiment.

You need to divide data into two distinct datasets.

Which module should you use?

133. HOTSPOT

You are using Azure Machine Learning to train machine learning models. You need a compute target on which to remotely run the training script.

You run the following Python code:

134. 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?

135. HOTSPOT

You create an Azure Machine Learning workspace and a dataset. The dataset includes age values for a large group of diabetes patients. You use the dp.mean function from the SmartNoise library to calculate the mean of the age value. You store the value in a variable named age.mean.

You must output the value of the interval range of released mean values that will be returned 95 percent of the time.

You need to complete the code.

Which code values should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

136. HOTSPOT

You manage an Azure Machine Learning workspace.

You must define the execution environments for your jobs and encapsulate the dependencies for your code.

You need to configure the environment from a Docker build context.

How should you complete the rode segment? To answer, select the appropriate option in the answer area. NOTE: Each correct selection is worth one point.

137. You manage an Azure Machine Learning workspace. You use Azure Machine Learning Python SDK v2 to configure a trigger to schedule a pipeline job. You need to create a time-based schedule with recurrence pattern.

Which two properties must you use to successfully configure the trigger? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.