DP-100 · Question #233
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…
The correct answer is B. No. The answer is No because the solution uses an incorrect method to log a collection of unique label values as metrics. The Azure ML run context's run.log() method logs a single scalar value per call and does not correctly handle a list or array of values as a single metric. To…
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Options
- AYes
- BNo
How the community answered
(16 responses)- A31% (5)
- B69% (11)
Explanation
The answer is No because the solution uses an incorrect method to log a collection of unique label values as metrics. The Azure ML run context's run.log() method logs a single scalar value per call and does not correctly handle a list or array of values as a single metric. To log a list of values (the unique labels), you must use run.log_list('label_column_unique_values', list_of_values), which is specifically designed to record multiple values under one metric name so they appear correctly in the experiment run history.
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