Free Microsoft DP-100 Practice Exam with Questions & Answers

You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.

The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must identify the feature that has the most influence on the predictions of the model for the second highest scoring algorithm. You must minimize the effort and time to identify the feature.

You need to complete the identification.

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 have an Azure Machine Learning workspace.

You plan to use the workspace to set up automated machine learning training for an image classification model.

You need to choose the primary metric to optimize the model training.

Which primary metric should you choose?

You use Azure Machine Learning studio to analyze a dataset containing a decimal column named column1. You need to verity that the column1 values are normally distributed.

Which static should you use?

: 215

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 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 have an Azure subscription that contains a resource group named rg-ml.

You plan to create an Azure Machine Learning workspace named workspacel in rg-ml by using Azure Machine Learning Python SDK v2.

You need to ensure workspacel is configured to prevent the collection of potentially sensitive data by Microsoft diagnostics.

How should you complete the provided code? To answer, select the appropnate options in the answer area.

NOTE: Each correct selection is worth one point.

You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.

You must use Hyperdrive to try combinations of the following hyperparameter values:

• learning_rate: any value between 0.001 and 0.1

• batch_size: 16, 32, or 64

You need to configure the search space for the Hyperdrive experiment.

Which two parameter expressions should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace. You build automated machine learning training experiments for computer vision models.

You need to use a primary metric for model optimization and hyperparameter tuning for each model.

Which primary metrics should you use for the models? To answer, move the appropriate primary metrics to the correct computer vision models. You may use each primary metric once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

You train a machine learning model by using Aunt Machine Learning.

You use the following training script m Python to log an accuracy value.

You must use a Python script to define a sweep job.

You need to provide the primary metric and goal you want hyper parameter tuning to optimize.

How should you complete the Python script? To answer select the appropriate 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 train and register an Azure Machine Learning model.

You plan to deploy the model to an online end point.

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution:

Create a Kubernetes online endpoint and set the value of its auth-mode parameter to amyl Token. Deploy the model to the online endpoint.

Does the solution meet the goal?

You manage an Azure Machine learning workspace.

You build a custom model you must log with Mlftow. The custom model includes the following:

• The model is not natively supported by Mlflow.

• The model cannot be serialized in Pickle format.

• The model source code is complex.

• The Python library tor the model must be packaged with the model.

You need to create a custom model flavor to enable logging with ML. flow.

What should you use?