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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:
 
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:
run.log_list('Label Values', label_vals)
Does the solution meet the goal?

A. Yes

B. No












 

Suggested Answer: A

run.log_list log a list of values to the run with the given name using log_list.
Example: run.log_list("accuracies", [0.6, 0.7, 0.87])
Note:
Data= pd.read_csv('data.csv')
Data is read into a pandas.DataFrame, which is a two-dimensional, size-mutable, potentially heterogeneous tabular data. label_vals =data['label'].unique label_vals contains a list of unique label values.
Reference:
https://www.element61.be/en/resource/azure-machine-learning-services-complete-toolbox-ai
 https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run(class)
 https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html

This question is in DP-100 Exam
For getting Microsoft Azure Data Scientist Associate Certificate


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