Microsoft Exam DP-100 Topic 2 Question 93 Discussion

Actual exam question for Microsoft's DP-100 exam

Question #: 93
Topic #: 2

[All DP-100 Questions]

You manage an Azure Machine Learning workspace.

You must provide explanations for the behavior of the models with feature importance measures.

You need to configure a Responsible Al dashboard in Azure Machine Learning.

Which dashboard component should you configure?

AFairness assessment

BCounterfactual what-if

CInterpretability

DCasual inference

Show Suggested Answer

Suggested Answer: C

by Daniela at Dec 08, 2023, 07:05 AM

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Otis

10 months ago

Hmm, this is a tricky one. Personally, I'm leaning towards 'Interpretability' since that's all about explaining the behavior of the models. But 'Causal inference' could also be an interesting choice. Guess we'll have to see what the experts say!

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Dante

10 months ago

Sounds good, we can always adjust if needed.

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Shelba

10 months ago

Let's go with Interpretability for now and see how it goes.

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Judy

10 months ago

So, should we go with Interpretability or Fairness assessment?

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Kathrine

10 months ago

True, ensuring fairness in models is crucial.

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Pearlie

10 months ago

But Fairness assessment could also be important to consider.

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Lillian

10 months ago

I agree, it helps explain the behavior of the models.

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Lorean

10 months ago

I think Interpretability is the way to go.

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Adolph

10 months ago

Responsible AI dashboard, eh? I'm guessing it's probably the Fairness assessment component, since that's all about ensuring your models aren't discriminating. But who knows, maybe there's a sneaky 'Counterfactual what-if' in there somewhere.

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German

10 months ago

Oof, feature importance measures, huh? That's a tough one. I bet the answer has something to do with interpretability, but let's see what the others think.

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Blondell

10 months ago

Whoa, this question is really hitting the nail on the head! Responsible AI is such a crucial topic these days. I'm definitely going to have to think this one through carefully.

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