Databricks Exam Databricks-Machine-Learning-Professional Topic 2 Question 22 Discussion

Actual exam question for Databricks's Databricks-Machine-Learning-Professional exam

Question #: 22
Topic #: 2

[All Databricks-Machine-Learning-Professional Questions]

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 of the following MLflow operations can the machine learning engineer use to accomplish this task?

Amlflow.register_model

BMlflowClient.update_registered_model

Cmlflow.add_model_version

DMlflowClient.get_model_version

EThe machine learning engineer needs to create an entirely new MLflow Model Registry model

Show Suggested Answer

Suggested Answer: B

by Casie at Aug 06, 2024, 04:19 PM

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Douglass

3 months ago

I'm still trying to figure out how to get the model to work in the first place. This versioning stuff is making my head spin. *sighs*

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Lenna

2 months ago

B: Yeah, that's a good starting point. It helps with adding new versions to the model.

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Laurene

2 months ago

A: Don't worry, it can be confusing at first. Have you tried using mlflow.register_model?

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Daisy

3 months ago

The machine learning engineer should just create a new model entirely. E) is the way to go, who needs version control anyway? *laughs*

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Blair

3 months ago

I'm pretty sure the answer is B) MlflowClient.update_registered_model. That's the function to update an existing model in the registry, right?

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Charlette

3 months ago

Hmm, I'm not sure about that. I was thinking C) mlflow.add_model_version might be the way to go. But I could be wrong, let me double-check the docs.

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Shizue

3 months ago

I think the correct answer is A) mlflow.register_model. That's the function to add a new version of an existing model to the MLflow Model Registry.

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Annamae

3 months ago

C) mlflow.add_model_version is also a valid option for adding a new version of the model to the MLflow Model Registry.

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Teddy

3 months ago

A) mlflow.register_model is the correct answer. It allows the engineer to add a new version of the model to the MLflow Model Registry.

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Ashleigh

3 months ago

I think the machine learning engineer needs to create an entirely new MLflow Model Registry model based on the options provided.

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Alfred

4 months ago

I'm not sure, but I think mlflow.register_model could also be used to accomplish the task.

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Jesusa

4 months ago

I agree with Julie, mlflow.add_model_version seems like the right operation to use in this case.

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Julie

4 months ago

I think the machine learning engineer can use mlflow.add_model_version to add a new version of the model.

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