Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure Exam Practice Test

You retrain an existing model.

You need to register the new version of a model while keeping the current version of the model in the registry.

What should you do?

You create a multi-class image classification deep learning model that uses the PyTorch deep learning

framework.

You must configure Azure Machine Learning Hyperdrive to optimize the hyperparameters for the classification model.

You need to define a primary metric to determine the hyperparameter values that result in the model with the best accuracy score.

Which three actions must you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

You are a data scientist working for a bank and have used Azure ML to train and register a machine learning model that predicts whether a customer is likely to repay a loan.

You want to understand how your model is making selections and must be sure that the model does not violate government regulations such as denying loans based on where an applicant lives.

You need to determine the extent to which each feature in the customer data is influencing predictions.

What should you do?

You have a comma-separated values (CSV) file containing data from which you want to train a classification model.

You are using the Automated Machine Learning interface in Azure Machine Learning studio to train the

classification model. You set the task type to Classification.

You need to ensure that the Automated Machine Learning process evaluates only linear models.

What should you do?

You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure Machine Learning SDK.

You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute.

You define a DataReference object by running the following code:

You need to load the training data.

Which code segment should you use?

You arc creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data.

You need to select a data cleaning method.

Which method 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 are creating a model to predict the price of a student's artwork depending on the following variables: the student's length of education, degree type, and art form.

You start by creating a linear regression model.

You need to evaluate the linear regression model.

Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error, Accuracy, Precision, Recall, F1 score, and AUC.

Does the solution meet the goal?