Microsoft DP-100 Practice Test - Questions Answers, Page 14

You are performing feature engineering on a dataset.

You must add a feature named CityName and populate the column value with the text London.

You need to add the new feature to the dataset.

Which Azure Machine Learning Studio module should you use?

You are evaluating a completed binary classification machine learning model.

You need to use the precision as the evaluation metric.

Which visualization should you use?

You are solving a classification task.

You must evaluate your model on a limited data sample by using k-fold cross-validation. You start by configuring a k parameter as the number of splits.

You need to configure the k parameter for the cross-validation.

Which value should you use?

You use the Azure Machine Learning service to create a tabular dataset named training_data. You plan to use this dataset in a training script.

You create a variable that references the dataset using the following code:

training_ds = workspace.datasets.get("training_data")

You define an estimator to run the script.

You need to set the correct property of the estimator to ensure that your script can access the training_data dataset.

Which property should you set?

You register a file dataset named csv_folder that references a folder. The folder includes multiple comma-separated values (CSV) files in an Azure storage blob container.

You plan to use the following code to run a script that loads data from the file dataset. You create and instantiate the following variables:

You have the following code:

You need to pass the dataset to ensure that the script can read the files it references.

Which code segment should you insert to replace the code comment?

You are creating a new Azure Machine Learning pipeline using the designer.

The pipeline must train a model using data in a comma-separated values (CSV) file that is published on a website. You have not created a dataset for this file.

You need to ingest the data from the CSV file into the designer pipeline using the minimal administrative effort.

Which module should you add to the pipeline in Designer?

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?

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 create an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:

/data/2018/Q1.csv

/data/2018/Q2.csv

/data/2018/Q3.csv

/data/2018/Q4.csv

/data/2019/Q1.csv

All files store data in the following format:

id,f1,f2,I

1,1,2,0

2,1,1,1

3,2,1,0

4,2,2,1

You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

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 create an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:

/data/2018/Q1.csv

/data/2018/Q2.csv

/data/2018/Q3.csv

/data/2018/Q4.csv

/data/2019/Q1.csv

All files store data in the following format:

id,f1,f2,I

1,1,2,0

2,1,1,1

3,2,1,0

4,2,2,1

You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

Solution: Run the following code:

Does the solution meet the goal?