Microsoft Exam DP-100 Topic 1 Question 107 Discussion

Actual exam question for Microsoft's DP-100 exam

Question #: 107
Topic #: 1

[All DP-100 Questions]

You manage an Azure Machine Learning workspace.

You must log multiple metrics by using MLflow.

You need to maximize logging performance.

What are two possible ways to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

AMLflowClient.log_batch

Bmlflowlog_metrics

Cmlflow.log_param

Dmlflow.log. metric

Show Suggested Answer

Suggested Answer: A, B

by Mitzie at Jul 07, 2024, 12:52 AM

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Kimbery

4 months ago

Trick question! The real answer is to use a Ouija board to summon the ghost of MLflow's creator. They'll know the secrets to maximum logging performance.

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Thurman

3 months ago

D) mlflow.log. metric

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Norah

3 months ago

C) mlflow.log_param

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Lazaro

4 months ago

A) MLflowClient.log_batch

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Bronwyn

4 months ago

Hmm, I'm torn between A and D. Batch logging or individual metrics? Decisions, decisions.

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Felton

4 months ago

I personally prefer option C) mlflow.log_param because it allows for logging parameters along with metrics, which can be useful for analysis.

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Bambi

5 months ago

Wait, you can use a Ouija board with Azure ML? Mind. Blown.

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Blondell

4 months ago

C) mlflow.log_param

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Johnetta

4 months ago

A) MLflowClient.log_batch

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Belen

4 months ago

C) mlflow.log_param

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Keneth

4 months ago

A) MLflowClient.log_batch

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Luz

5 months ago

That's a good point, but I still think option A) is more efficient for logging multiple metrics in batches.

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Titus

5 months ago

Option A looks like the way to go. Batch logging is the key to maximizing performance.

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Dalene

4 months ago

Yeah, it helps maximize performance for sure.

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Fredric

4 months ago

I agree, batch logging is definitely the way to go.

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Ceola

5 months ago

I disagree, I believe option D) mlflow.log_metric is the better choice because it directly logs the metric.

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Luz

5 months ago

I think option A) MLflowClient.log_batch is the way to go for maximizing logging performance.

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