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Microsoft

DP-100 · Question #147

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…

The correct answer is E. import os import argparse import pandas as pd parser = argparse.ArgumentParser() parser.add_argument('--data-folder', type=str, dest='data_folder') data_folder = args.data_folder data = pd.read_csv(os.path.join(data_folder, 'ml_data', 'data_folder', 'train', 'data.csv')). data_folder = args.data_folder # Load Train and Test data train_data = pd.read_csv(os.path.join(data_folder, 'data.csv'))

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Question

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? A. B. C. D. E.

Exhibits

DP-100 question #147 exhibit 1
DP-100 question #147 exhibit 2
DP-100 question #147 exhibit 3
DP-100 question #147 exhibit 4
DP-100 question #147 exhibit 5

Options

  • Aimport os import argparse import pandas as pd parser = argparse.ArgumentParser() parser.add_argument('--data-folder', type=str, dest='data_folder') data_folder = args.data_folder data = pd.read_csv(os.path.join(data_folder, 'ml-data', 'train_data', 'data.csv'))
  • Bimport os import argparse import pandas as pd parser = argparse.ArgumentParser() parser.add_argument('--data-folder', type=str, dest='data_folder') data_folder = args.data_folder data = pd.read_csv(os.path.join(data_folder, 'train', 'data.csv'))
  • Cimport pandas as pd data = pd.read_csv('./data.csv')
  • Dimport os import argparse import pandas as pd parser = argparse.ArgumentParser() parser.add_argument('--data-folder', type=str, dest='data_folder') data_folder = args.data_folder data = pd.read_csv(os.path.join(data_folder, 'data_folder', 'data.csv'))
  • Eimport os import argparse import pandas as pd parser = argparse.ArgumentParser() parser.add_argument('--data-folder', type=str, dest='data_folder') data_folder = args.data_folder data = pd.read_csv(os.path.join(data_folder, 'ml_data', 'data_folder', 'train', 'data.csv'))

How the community answered

(35 responses)
  • A
    3% (1)
  • B
    6% (2)
  • C
    11% (4)
  • D
    3% (1)
  • E
    77% (27)

Explanation

data_folder = args.data_folder # Load Train and Test data train_data = pd.read_csv(os.path.join(data_folder, 'data.csv'))

Topics

#Azure Machine Learning SDK#DataReference#Data loading#Local compute

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