Free Microsoft DP-100 Exam Questions

An organization creates and deploys a multi-class image classification deep learning model that uses a set of labeled photographs. The software engineering team reports there is a heavy inferencing load for the prediction web services during the summer. The production web service for the model fails to meet demand despite having a fully-utilized compute cluster where the web service is deployed. You need to improve performance of the image classification web service with minimal downtime and minimal administrative effort. What should you advise the IT Operations team to do?

You create an Azure Machine Learning workspace. You must create a custom role named DataScientist that meets the following requirements: Role members must not be able to delete the workspace. Role members must not be able to create, update, or delete compute resource in the workspace. Role members must not be able to add new users to the workspace. You need to create a JSON file for the DataScientist role in the Azure Machine Learning workspace. The custom role must enforce the restrictions specified by the IT Operations team. Which JSON code segment should you use?

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?

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 Apply Transformation module. Does the solution meet the goal?

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.