Databricks Machine Learning Professional Question 75
Select 3A data science team is using the Databricks Model Registry to manage their machine learning models. The team wants to ensure that they can track different versions of a model, assign stages (e.g., Staging, Production), and record relevant metadata. Which of the following are key user interactions supported by the Databricks Model Registry?
- A
Register a new model or model version in the Model Registry.
- B
Manually tune hyperparameters of the model directly within the Model Registry.
- C
Transition a model to different stages, such as Staging or Production.
- D
Add comments or descriptions to models and versions for better collaboration.
- E
Deploy models directly from the Model Registry to a production environment.
Show answer and explanation
Correct answers: A, C, D
Explanation
The Databricks Model Registry is a centralized system for managing the lifecycle of machine learning models. Key interactions include registering models, transitioning models between stages, and adding metadata for collaboration. It does not directly support hyperparameter tuning or direct deployment but integrates with other workflows to assist in these tasks.
- A. Correct.
Correct: Registering a new model or model version is a fundamental feature of the Databricks Model Registry, allowing users to manage and version their models effectively.
- B. Incorrect.
Incorrect: The Model Registry is not designed for tuning hyperparameters; this step is typically performed during the model training process, not within the registry.
- C. Correct.
Correct: Transitioning models to different stages (e.g., Staging, Production) is a key functionality of the Model Registry, enabling clear lifecycle management.
- D. Correct.
Correct: Users can add comments or descriptions to models in the registry, which facilitates collaboration among team members and improves transparency.
- E. Incorrect.
Incorrect: While the Model Registry supports deployment workflows, it does not directly deploy models; deployment typically involves integration with other tools or systems.