Databricks Machine Learning Professional Exam - Topic 6 Question 23 Discussion

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

Question #: 23
Topic #: 6

[All Databricks Machine Learning Professional Questions]

A data scientist has developed a scikit-learn random forest model model, but they have not yet logged model with MLflow. They want to obtain the input schema and the output schema of the model so they can document what type of data is expected as input.

Which of the following MLflow operations can be used to perform this task?

Amlflow.models.schema.infer_schema

Bmlflow.models.signature.infer_signature

Cmlflow.models.Model.get_input_schema

Dmlflow.models.Model.signature

EThere is no way to obtain the input schema and the output schema of an unlogged model.

Show Suggested Answer

Suggested Answer: A

by Jaclyn at Aug 23, 2024, 02:33 PM

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Desiree

4 months ago

I thought you needed to log the model first to access any schema info.

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Dortha

5 months ago

Wait, can you really get schemas from an unlogged model?

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Lindsey

5 months ago

I disagree, it has to be C, get_input_schema.

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Bulah

5 months ago

Definitely B, mlflow.models.signature.infer_signature!

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Ricki

5 months ago

I think it's A, mlflow.models.schema.infer_schema.

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Danica

6 months ago

I vaguely recall that C is about getting the input schema directly, but I’m not confident if it applies to unlogged models.

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Mira

6 months ago

I practiced a similar question before, and I feel like E could be a trick option since it mentions unlogged models.

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Ozell

6 months ago

I'm not entirely sure, but I remember something about A being used for schema inference. It could be that one?

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Dolores

6 months ago

I think the answer might be B, because it sounds like it relates to inferring the model's signature, which includes input and output schemas.

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Sabra

6 months ago

I'm pretty confident that the answer is B. The `mlflow.models.signature.infer_signature` function is specifically designed to infer the input and output schemas of a model, regardless of whether it's been logged to MLflow or not. This seems like the most straightforward solution for the given problem.

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Frank

6 months ago

I'm a bit confused by this question. I thought we needed to log the model to MLflow first before we could access any information about it. Is there really a way to get the schemas without logging the model? I'll have to think this through carefully.

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Jess

6 months ago

Option B sounds like the right choice here. The question is asking about obtaining the input and output schemas, and the `infer_signature` function is designed to do just that, even for unlogged models.

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Norah

6 months ago

Hmm, I'm not sure about this one. I know we can use MLflow to log models and get information about them, but I'm not familiar with the specific functions for getting the input and output schemas. I'll have to review the MLflow documentation to see which option is correct.

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Cherelle

6 months ago

I think the answer is B. The `mlflow.models.signature.infer_signature` function should be able to infer the input and output schemas of the model, even if it hasn't been logged to MLflow yet.

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Francene

6 months ago

Hmm, I'm a bit confused by the options here. I'm not sure which one would be the simplest solution for frequent catalog changes. Maybe I should review the Magento documentation again.

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