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?
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 a data scientist using Azure Machine Learning Studio.
You need to normalize values to produce an output column into bins to predict a target column.
Solution: Apply a Quantiles normalization with a QuantileIndex normalization.
Does the solution meet the GOAL?
You create an Azure Machine learning workspace. The workspace contains a folder named src. The folder contains a Python script named script 1 .py.
You use the Azure Machine Learning Python SDK v2 to create a control script. You must use the control script to run script l.py as part of a training job.
You need to complete the section of script that defines the job parameters.
How should you complete the script? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You manage an Azure Al Foundry project.
You deploy a large language model from the model catalog.
You need to manually evaluate the model, collect the statistics, and be able to review the results later.
You manage an Azure Machine Learning workspace. You develop a regression model training pipeline by using Notebooks. You need to determine the appropriate evaluation metric for the experiment.
Which two metrics should you choose? Each correct answer presents a complete solution. Choose two. NOTE: Each correct selection is worth one point.
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?
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: Create an instance of the MICIient class.
Does the solution meet the goal?
You manage an Azure OpenAI Service deployment of the gpt-4o-mini base model.
You plan to fine-tune the deployed model by using OpenAI Python la code. In the code, you import all required Python libraries and create a sample training data set.
You need to complete the next section of the code to estimate the cost of fine-tuning by using the sample training data set.
How should you complete the code section? To answer, select the appropnate options in the answer area.
NOTE: Each correct selection is worth one point.
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?
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?
