A data scientist would like to enable MLflow Autologging for all machine learning libraries used in a notebook. They want to ensure that MLflow Autologging is used no matter what version of the Databricks Runtime for Machine Learning is used to run the notebook and no matter what workspace-wide configurations are selected in the Admin Console.
Which of the following lines of code can they use to accomplish this task?

• A.It is not possible to automatically log MLflow runs.
• B.mlflow.sklearn.autolog()
• C.spark.conf.set("autologging", True)
• D.mlflow.spark.autolog()
• E.mlflow.autolog()

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In a Spark ML Pipeline, what is the role of a Transformer?

• A.Fits data
• B.Converts datasets into new datasets
• C.Trains models
• D.Evaluates models

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A Data Scientist needs to analyze drift detection results from Databricks Lakehouse Monitoring.
The system has generated both profile metrics and drift metrics tables. The scientist needs to identify baseline drift in numerical features by comparing current data against a baseline from 6 months ago. Which combination of table columns and values indicates baseline drift in a numerical feature?

• A.window_cmp pointing to baseline time window and tv_distance > 0.5 with any drift_type value.
• B.drift_type = "BASELINE", chi_squared_test.p_value < 0.05, and js_distance > 0.2.
• C.drift_type = "BASELINE", ks_test.p_value < 0.05, and wasserstein_distance > 0.1.
• D.log_type = "BASELINE" in profile metrics table with population_stability_index > 0.2 in drift metrics table.

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Which of the following describes the concept of MLflow Model flavors?

• A.A convention that deployment tools can use to understand the model
• B.A convention that MLflow Model Registry can use to organize its Models by project
• C.A convention that MLflow Model Registry can use to version models
• D.A convention that MLflow Experiments can use to organize their Runs by project
• E.A convention that deployment tools can use to wrap preprocessing logic into a Model

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A machine learning engineer is manually refreshing a model in an existing machine learning pipeline. The pipeline uses the MLflow Model Registry model "project". The machine learning engineer would like to add a new version of the model to "project". Which MLflow operation can the machine learning engineer use to accomplish this task?

• A.The machine learning engineer needs to create an entirely new MLflow Model Registry model
• B.mlflow.add_model_version
• C.MlflowClient.get_model_version
• D.MlflowClient.update_registered_model
• E.mlflow.register_model

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