DP-100 Exam Dumps : Designing and Implementing a Data Science Solution on Azure

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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.

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You train a classification model by using a logistic regression algorithm.

You must be able to explain the model’s predictions by calculating the importance of each feature, both as an overall global relative importance value and as a measure of local importance for a specific set of predictions.

You need to create an explainer that you can use to retrieve the required global and local feature importance values.

Solution: Create a MimicExplainer.

Does the solution meet the goal?

You manage an Azure Machine Learning workspace named workspaces

You plan to create a registry named registry01 with the help of the following registry.yml (line numbers are used for reference only):

You need to use Azure Machine Learning Python SDK v2 with Python 3.10 in a notebook to interact with workspace1.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

You are using Azure Machine Learning to monitor a trained and deployed model. You implement Event Grid to respond to Azure Machine Learning events.

Model performance has degraded due to model input data changes.

You need to trigger a remediation ML pipeline based on an Azure Machine Learning event.

Which event should you use?