Free Designing and Implementing a Data Science Solution on Azure DP-100 Exam Practice Test

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 AksWebservice instance.Set the value of the auth_enabled property to True.Deploy the model to the service.Does the solution meet the goal?

• Yes
• No

You are building a machine learning model for translating English language textual content into Frenchlanguage textual content.You need to build and train the machine learning model to learn the sequence of the textual content.Which type of neural network should you use?

• Multilayer Perceptions (MLPs)
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Generative Adversarial Networks (GANs)

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?

• normalized_mean_absolute_error
• [spearman_correlation
• AUC.weighted
• accuracy
• normalized_root_mean_squared_error

You manage an Azure Machine Learning workspace named workspacesYou 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?

• Synapse workspace web URL and Spark pool name
• resource ID of the Synapse Spark pool and a user-defined name
• pool URL of the Synapse Spark pool and a system-assigned name
• Synapse workspace name and workspace web URL

You use the Azure Machine learning SDK foe Python to create a pipeline that includes the following step:The output of the step run must be cached and reused on subsequent runs when the source.directory value has not changed.You need to define the step.What should you include in the step definition?

• allow.reuse
• hash_path
• data-as_input(name-)
• version

You plan to use a Deep Learning Virtual Machine (DLVM) to train deep learning models using Compute Unified Device Architecture (CUDA) computations.You need to configure the DLVM to support CUDA.What should you implement?

• Intel Software Guard Extensions (Intel SGX) technology
• Solid State Drives (SSD)
• Graphic Processing Unit (GPU)
• Computer Processing Unit (CPU) speed increase by using overcloking
• High Random Access Memory (RAM) configuration

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?

• process_count_per_node= '6'
• node_count= '6'
• mini_batch_size= '6'
• error_threshold= '6'

You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder.The experiment fails.You need to troubleshoot the failed experiment.What are two possible ways to achieve this goal? Each correct answer presents a complete solution.

• Use the get_metrics() method of the run object to retrieve the experiment run logs.
• Use the get_details_with_logs() method of the run object to display the experiment run logs.
• View the log files for the experiment run in the experiment folder.
• View the logs for the experiment run in Azure Machine Learning studio.
• Use the get_output() method of the run object to retrieve the experiment run logs.

You use the following code to define the steps for a pipeline:from azureml.core import Workspace, Experiment, Runfrom azureml.pipeline.core import Pipelinefrom azureml.pipeline.steps import PythonScriptStepws = 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.

• experiment = Experiment(workspace=ws, name='pipeline-experiment') run = experiment.submit(config=pipeline_steps)
• run = Run(pipeline_steps)
• pipeline = Pipeline(workspace=ws, steps=pipeline_steps) experiment = Experiment(workspace=ws, name='pipeline-experiment') run = experiment.submit(pipeline)
• pipeline = Pipeline(workspace=ws, steps=pipeline_steps) run = pipeline.submit(experiment_name='pipeline-experiment')

You manage an Azure Machine Learning workspace named projlYou plan to use assets defined in projl to create a pipeline in the Machine Learning studio designerYou need to set the Registry name filter to display only the list of assets defined in projl.What should you set the Registry name filter to?

• proj1
• workspace
• azureml-meta
• azureml