Databricks Certified Machine Learning Associate Practice Mode

Community Discussion

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• Chose A0

  - Correct answer : A — Call `mlflow.log_metric("val_accuracy", value, step=epoch)` once per epoch, passing the epoch number as `step` so the metric history builds one point per epoch. A . This is correct because passing an explicit `step` value on each call is exactly how MLflow builds a per-step metric history for a key, which the UI then renders as a trend line across epochs. B . This is incorrect because omitting `step` logs every call at the default step of 0, so repeated calls create multiple points stacked at the same step rather than a clean per-epoch trend. C . This is incorrect because parameters are meant for static configuration values, are not designed to accept repeated updates to the same key across a run, and are not charted as a time series in the UI. D . This is incorrect because uploaded files are stored as opaque artifacts; MLflow does not parse artifact contents and turn them into interactive metric charts.