Master Databricks-Machine-Learning-Professional Exam with Reliable Practice Questions

Which of the following is an advantage of using the python_function(pyfunc) model flavor over the built-in library-specific model flavors?

Which of the following lists all of the model stages are available in the MLflow Model Registry?

Which of the following MLflow Model Registry use cases requires the use of an HTTP Webhook?

A machine learning engineer wants to log and deploy a model as an MLflow pyfunc model. They have custom preprocessing that needs to be completed on feature variables prior to fitting the model or computing predictions using that model. They decide to wrap this preprocessing in a custom model class ModelWithPreprocess, where the preprocessing is performed when calling fit and when calling predict. They then log the fitted model of the ModelWithPreprocess class as a pyfunc model.

Which of the following is a benefit of this approach when loading the logged pyfunc model for downstream deployment?

A machine learning engineer wants to move their model version model_version for the MLflow Model Registry model model from the Staging stage to the Production stage using MLflow Client client. At the same time, they would like to archive any model versions that are already in the Production stage.

Which of the following code blocks can they use to accomplish the task?

A)

B)

C)

D)