Free Microsoft DP-100 Exam Questions

Question 1

A set of CSV files contains sales records. All the CSV files have the same data schema.

Each CSV file contains the sales record for a particular month and has the filename sales.csv. Each file in

stored in a folder that indicates the month and year when the data was recorded. The folders are in an Azure

blob container for which a datastore has been defined in an Azure Machine Learning workspace. The folders

are organized in a parent folder named sales to create the following hierarchical structure:

At the end of each month, a new folder with that month’s sales file is added to the sales folder.

You plan to use the sales data to train a machine learning model based on the following requirements:

You must define a dataset that loads all of the sales data to date into a structure that can be easily

converted to a dataframe.

You must be able to create experiments that use only data that was created before a specific previous

month, ignoring any data that was added after that month.

You must register the minimum number of datasets possible.

You need to register the sales data as a dataset in Azure Machine Learning service workspace.

What should you do?

A : Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset each month, replacing theexisting dataset and specifying a tag named month indicating the month and year it was registered. Usethis dataset for all experiments.

B : Create a tabular dataset that references the datastore and specifies the path 'sales/*/sales.csv', register thedataset with the name sales_dataset and a tag named month indicating the month and year it wasregistered, and use this dataset for all experiments.

C : Create a new tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset_MM-YYYY each monthwith appropriate MM and YYYY values for the month and year. Use the appropriate month-specificdataset for experiments.

D : Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file. Register the dataset with the name sales_dataset each month as a new version and with atag named month indicating the month and year it was registered. Use this dataset for all experiments,identifying the version to be used based on the month tag as necessary.

Answer: B

Question 2

You use Azure Machine Learning Designer to load the following datasets into an experiment: Dataset1You use Azure Machine Learning Designer to load the following datasets into an experiment: You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets. Solution: Use the Join Data component. Does the solution meet the goal?

A : Yes

B : No

Answer: B

Question 3

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?

A : vironment_definition = {"training_data":training_ds}

B : puts = [training_ds.as_named_input('training_ds')]

C : ript_params = {"--training_ds":training_ds}

D : urce_directory = training_ds

Answer: B

Question 4

You create an Azure Machine Learning workspace. The workspace contains a dataset named sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline that will prepare data in the dataset and then train and register a model based on the prepared data. The first stage of the pipeline contains the following code:You need to identify the location containing the output of the first stage of the script that you can use as input for the second stage. Which storage location should you use?

A : workspaceblobstore datastore

B : workspacefi lest ore datastore

C : compute instance

Answer: C

Question 5

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 use Azure Machine Learning designer to load the following datasets into an experiment:You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets. Solution: Use the Apply Transformation module. Does the solution meet the goal?

A : Yes

B : No

Answer: B