DP-100 Exam Dumps : Designing and Implementing a Data Science Solution on Azure

You have an Azure Machine Learning workspace and a data source file ./data/cc_data.csv in the local storage.

You plan to use Azure Machine Learning Python SDK v2 to store the content of the cc.data.csv file in a data asset named cc_data_asset in the workspace.

You write code to connect to the workspace and import all required libraries.

You need to complete the remaining code to ensure it will result in the cc_data_asset that contains the data from cc_data.csv.

How should you complete the code? 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 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,M,f2,l

1,1,2,0

2,1,1,1

32,10

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?

You are with a time series dataset in Azure Machine Learning Studio.

You need to split your dataset into training and testing subsets by using the Split Data module.

Which splitting mode should you use?