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Databricks Machine Learning Professional Exam - Topic 1 Question 7 Discussion

A machine learning engineer has deployed a model recommender using MLflow Model Serving. They now want to query the version of that model that is in the Production stage of the MLflow Model Registry.Which of the following model URIs can be used to query the described model version?
B) The version number of the model version in Production is necessary to complete this task.
A) https://<databricks-instance>/model-serving/recommender/Production/invocations
C) https://<databricks-instance>/model/recommender/stage-production/invocations
D) https://<databricks-instance>/model-serving/recommender/stage-production/invocations
E) https://<databricks-instance>/model/recommender/Production/invocations

Databricks Machine Learning Professional Exam - Topic 1 Question 7 Discussion

Actual exam question for Databricks's Databricks Machine Learning Professional exam
Question #: 7
Topic #: 1
[All Databricks Machine Learning Professional Questions]

A machine learning engineer has deployed a model recommender using MLflow Model Serving. They now want to query the version of that model that is in the Production stage of the MLflow Model Registry.

Which of the following model URIs can be used to query the described model version?

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Suggested Answer: B

by Clay at Dec 26, 2023, 03:53 AM

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Dianne
8 months ago
E is also a valid URI, but I prefer A for clarity.
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Shaun
8 months ago
Wait, can you really use "stage-production"? That sounds off.
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Helga
8 months ago
Definitely leaning towards D, seems like the right format.
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Eliz
8 months ago
I think B is important too, you need the version number!
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Linn
8 months ago
Option A looks correct for querying the model in Production.
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Vallie
9 months ago
I’m leaning towards option D, but I’m a bit confused about whether "stage-production" is the correct phrasing in this context.
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Nickolas
9 months ago
I practiced a similar question, and I feel like the version number might not be necessary for this specific query.
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Ricarda
9 months ago
I think option A looks familiar; it seems like the correct format for querying a model in production.
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Clorinda
9 months ago
I remember we discussed the importance of the model URI structure in MLflow, but I'm not sure if "stage-production" is the right term to use.
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Judy
9 months ago
I'm leaning towards C. The URI in that option has the "stage-production" part, which seems to match what the question is asking for.
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Johnetta
9 months ago
Hmm, I'm a bit confused. The question mentions MLflow Model Serving, but the URIs don't seem to match the typical format for that. I'll need to double-check the MLflow documentation to be sure.
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Frederick
9 months ago
I think the answer is E. The question specifically mentions querying the model version in the Production stage, and the URI in option E looks like it would match that requirement.
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Iola
9 months ago
Option B seems like the safest bet here. The question says the version number is necessary, so I'd want to make sure I have that information before trying to query the model.
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Alva
9 months ago
The Individual-Moving Range charts seem like they could work well for handling outliers in continuous data with subgroups.
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