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Free DP-100 Exam Braindumps (page: 17)

Page 16 of 127
PDF with 512 Questions

HOTSPOT (Drag and Drop is not supported)
You are retrieving data from a large datastore by using Azure Machine Learning Studio.
You must create a subset of the data for testing purposes using a random sampling seed based on the system clock.
You add the Partition and Sample module to your experiment.
You need to select the properties for the module.
Which values should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:


Box 1: Sampling
Create a sample of data
This option supports simple random sampling or stratified random sampling. This is useful if you want to create a smaller representative sample dataset for testing.
1. Add the Partition and Sample module to your experiment in Studio, and connect the dataset.
2. Partition or sample mode: Set this to Sampling.
3. Rate of sampling. See box 2 below.
Box 2: 0
3. Rate of sampling. Random seed for sampling: Optionally, type an integer to use as a seed value.
This option is important if you want the rows to be divided the same way every time. The default value is 0, meaning that a starting seed is generated based on the system clock. This can lead to slightly different results each time you run the experiment.


Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample



You are creating a machine learning model. You have a dataset that contains null rows.
You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset.
Which parameter should you use?

  1. Replace with mean
  2. Remove entire column
  3. Remove entire row
  4. Hot Deck
  5. Custom substitution value
  6. Replace with mode

Answer(s): C

Explanation:

Remove entire row: Completely removes any row in the dataset that has one or more missing values. This is useful if the missing value can be considered randomly missing.


Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data



HOTSPOT (Drag and Drop is not supported)
The finance team asks you to train a model using data in an Azure Storage blob container named finance-data.
You need to register the container as a datastore in an Azure Machine Learning workspace and ensure that an error will be raised if the container does not exist.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:


Box 1: register_azure_blob_container
Register an Azure Blob Container to the datastore.
Box 2: create_if_not_exists = False
Create the file share if it does not exist, defaults to False.


Reference:

https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.datastore.datastore



You plan to provision an Azure Machine Learning Basic edition workspace for a data science project.
You need to identify the tasks you will be able to perform in the workspace.
Which three tasks will you be able to perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  1. Create a Compute Instance and use it to run code in Jupyter notebooks.
  2. Create an Azure Kubernetes Service (AKS) inference cluster.
  3. Use the designer to train a model by dragging and dropping pre-defined modules.
  4. Create a tabular dataset that supports versioning.
  5. Use the Automated Machine Learning user interface to train a model.

Answer(s): A,C,E

Explanation:

Incorrect Answers:
C, E: The UI is included the Enterprise edition only.


Reference:

https://azure.microsoft.com/en-us/pricing/details/machine-learning/






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