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Free Microsoft DP-100 Exam Questions

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  • Microsoft DP-100 Exam Questions
  • Provided By: Microsoft
  • Exam: Microsoft Designing and Implementing a Data Science Solution on Azure
  • Certification: Microsoft Azure Data Scientist Associate
  • Total Questions: 525
  • Updated On: Jan 09, 2025
  • Rated: 4.9 |
  • Online Users: 1050
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  • Question 1
    • You use the Azure Machine Learning SDK to run a training experiment that trains a classification model and
      calculates its accuracy metric.
      The model will be retrained each month as new data is available.
      You must register the model for use in a batch inference pipeline.
      You need to register the model and ensure that the models created by subsequent retraining experiments are
      registered only if their accuracy is higher than the currently registered model.
      What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
      NOTE: Each correct selection is worth one point.


      Answer: A,C
  • Question 2
    • 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:
      162
      You need to load the training data.
      Which code segment should you use?

      Answer: A
  • Question 3
    • This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.
      You are planning to make use of Azure Machine Learning designer to train models.
      You need choose a suitable compute type.
      Recommendation: You choose Compute cluster.
      Will the requirements be satisfied?

      Answer: A
  • Question 4
    • 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 plan to use a Python script to run an Azure Machine Learning experiment. The script creates a reference
      to the experiment run context, loads data from a file, identifies the set of unique values for the label column,
      and completes the experiment run:
      from azureml.core import Run
      import pandas as pd
      run = Run.get_context()
      data = pd.read_csv('data.csv')
      label_vals = data['label'].unique()
      # Add code to record metrics here
      run.complete()
      The experiment must record the unique labels in the data as metrics for the run that can be reviewed later.
      You must add code to the script to record the unique label values as run metrics at the point indicated by the
      comment.
      Solution: Replace the comment with the following code:
      for label_val in label_vals:
      run.log('Label Values', label_val)
      Does the solution meet the goal?

      Answer: A
  • Question 5
    • You are preparing to train a regression model via automated machine learning. The data available to you has features with missing values, as well as categorical features with little discrete values. You want to make sure that automated machine learning is configured as follows: missing values must be automatically imputed. categorical features must be encoded as part of the training task. Which of the following actions should you take?

      Answer: A
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