Free Microsoft DP-100 Practice Exam with Questions & Answers

You need to identify the methods for dividing the data according, to the testing requirements.

Which properties should you select? To answer, select the appropriate option-, m the answer area. NOTE: Each correct selection is worth one point.

You plan to use automated machine learning by using Azure Machine Learning Python SDK v2 to train a regression model. You have data that has features with missing values, and categorical features with few distinct values.

You need to control whether automated machine learning automatically imputes missing values and encode categorical features as part of the training task. Which enemy of the autumn package should you use?

You create an Azure Machine learning workspace.

You are use the Azure Machine -learning Python SDK v2 to define the search space for concrete hyperparafneters. The hyper parameters must consist of a list of predetermined, comma-separated.

You need to import the class from the azure ai ml. sweep package used to create the list of values.

Which class should you import?

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 are using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model. You configure a HyperDriveConfig for the experiment by running the following code:

You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted.

Solution: Run the following code:

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 are analyzing a numerical dataset which contains missing values in several columns.

You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.

You need to analyze a full dataset to include all values.

Solution: Remove the entire column that contains the missing data point.

Does the solution meet the goal?

You are analyzing the asymmetry in a statistical distribution.

The following image contains two density curves that show the probability distribution of two datasets.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

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 run a script as an experiment in Azure Machine Learning.

You have a Run object named run that references the experiment run. You must review the log files that were generated during the experiment run.

You need to download the log files to a local folder for review.

Which two code segments can you run to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace That has an Azure Machine Learning datastore.

Data must be loaded from the following sources:

• a credential-less Azure Blob Storage

• an Azure Data Lake Storage (ADLS) Gen 2 which is not a credential-less datastore

You need to define the authentication mechanisms to access data in the Azure Machine Learning datastore.

Which data access mechanism should you use? To answer, move the appropriate data access mechanisms to the correct storage types. You may use each data access mechanism 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 model by using Azure Machine Learning. You use Azure Blob Storage to store production data.

The model must be re-trained when new data is uploaded to Azure Blob Storage. You need to minimize development and coding.

You need to configure Azure services to develop a re-training solution.

Which Azure services should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.