Databricks Machine Learning Professional Question 78: You are working on a Databricks project where you have trained a new... | Databricks Machine Learning Professional Dumps

Databricks Machine Learning Professional practice question 78 of 280

Databricks Certified Machine Learning Professional. Professional level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Professional Question 78

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You are working on a Databricks project where you have trained a new version of a machine learning model, and you want to programmatically register it in the Databricks Model Registry. Which of the following steps are necessary to successfully register the new model version?

A
Load the trained model as a PyFunc model and call the mlflow.register_model function with the model's URI and desired model name.
B
Specify the model name and call the mlflow.register_model function with the model's URI.
C
Use the mlflow.log_model function to log the model to MLflow first, and then use the mlflow.register_model function to register it.
D
Use the mlflow.models.Model.register function to directly register the trained model in the Model Registry.
E
Log the model using mlflow.log_model and then use the mlflow.client.MlflowClient.create_registered_model method to register it.

Show answer and explanation

Correct answers: B, C

Explanation

To programmatically register a new model version in the Databricks Model Registry, the model must first be logged to MLflow using mlflow.log_model. Once logged, the mlflow.register_model function can be used to register the model to the registry by specifying the model's URI and a desired model name. These steps ensure the model version is properly tracked and registered.

A. Incorrect.
Incorrect: There is no need to load the model as a PyFunc model before using the mlflow.register_model function. The model URI is sufficient for registration.
B. Correct.
Correct: The mlflow.register_model function requires the model's URI and the desired model name to register a new version in the Model Registry.
C. Correct.
Correct: Before registering a model, it must be logged to the MLflow tracking server using mlflow.log_model. Registration happens after logging.
D. Incorrect.
Incorrect: The mlflow.models.Model.register function does not exist in the MLflow API. This is an invalid option.
E. Incorrect.
Incorrect: While mlflow.client.MlflowClient.create_registered_model can create a new registered model, it does not register a specific model version to the registry. It is not the correct method for this use case.

Databricks Machine Learning Professional practice question 78 of 280

Databricks Machine Learning Professional Question 78

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