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You need to record the row count as a metric named row_count that can be returned using the get_metrics method of the Run object after the experiment run completes. Which code should you use?
Correct Answer: B
Log a numerical or string value to the run with the given name using log(name, value, description=''). Logging a metric to a run causes that metric to be stored in the run record in the experiment. You can log the same metric multiple times within a run, the result being considered a vector of that metric. Example: run.log("accuracy", 0.95) Incorrect Answers: E: Using log_row(name, description=None, **kwargs) creates a metric with multiple columns as described in kwargs. Each named parameter generates a column with the value specified. log_row can be called once to log an arbitrary tuple, or multiple times in a loop to generate a complete table. Example: run.log_row("Y over X", x=1, y=0.4) Reference: https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run