| Exam Name: | Designing and Implementing a Data Science Solution on Azure | ||
| Exam Code: | DP-100 Dumps | ||
| Vendor: | Microsoft | Certification: | Microsoft Azure |
| Questions: | 428 Q&A's | Shared By: | greyson |
You have an Azure Machine Learning workspace named WS1.
You plan to use the Responsible Al dashboard to assess MLflow models that you will register in WS1.
You need to identify the library you should use to register the MLflow models.
Which library 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: Pass the UserAssignedldentity class object to the SynapseSparkCompute class.
Does the solution meet the goat?
You use the Azure Machine Learning SDK to run a training experiment that trains a classification model and calculates its accuracy metric.
The model will be retrained each month as new data is available.
You must register the model for use in a batch inference pipeline.
You need to register the model and ensure that the models created by subsequent retraining experiments are registered only if their accuracy is higher than the currently registered model.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You are developing a machine learning model by using Azure Machine Learning. You are using multiple text files in tabular format for model data. You have the following requirements:
• You must use AutoML jobs to train the model.
• You must use data from specified columns.
• The data concept must support lazy evaluation.
You need to load data into a Pandas dataframe.
Which data concept should you use?
TESTED 21 Nov 2024
