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Microsoft DP-100 Exam Questions
- Topic 1: Design and prepare a machine learning solution: This section of the exam covers designing a machine learning solution, managing the Azure machine learning workspace, and managing data in the Azure machine learning environment.
- Topic 2: Explore data and train models: This section of the exam covers exploring data by utilizing data assets and establishing models by utilizing Azure's machine learning designer. It also covers using automated machine learning to explore optimal frameworks.
- Topic 3: Prepare a model for deployment: This section also covers running model training scripts, implementing training pipelines, and overseeing frameworks in Azure Machine Learning.
- Topic 4: Deploy and retrain a model: This section covers implementing a model and deploying machine learning operations and practices.
Free Microsoft DP-100 Exam Actual Questions
Note: Premium Questions for DP-100 were last updated On Dec. 10, 2024 (see below)
You use Azure Machine Learning Designer to load the following datasets into an experiment:
Data set 1
Dataset 2
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 Apply Transformation component.
Does the solution meet the goal?
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?
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?
You manage an Azure Machine Learning workspace. You plan to import data from Azure Data Lake Storage Gen2. You need to build a URI that represents the storage location. Which protocol should you use?
You manage an Azure Machine Learning workspace.
An MLflow model is already registered. You plan to customize how the deployment does inference. You need to deploy the MLflow model to a batch endpoint for batch inferencing. What should you create first?
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