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Microsoft DP-100 Exam - Topic 5 Question 88 Discussion

Actual exam question for Microsoft's DP-100 exam
Question #: 88
Topic #: 5
[All DP-100 Questions]

You use Azure Machine Learning to tram a model.

You must use Baylean sampling to Tune hyperparaters.

You need to select a learning_rate parameter distribution.

Which two distributions can you use? Each correct answer presents a complete solution.

NOTE Each correct selection is worth one point.

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Suggested Answer: B, C

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Herminia
4 months ago
I thought QNormal was a thing too, but not sure here.
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Paz
4 months ago
Uniform is also a good option, right?
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Gary
4 months ago
Wait, can we really use Normal for this? Seems off.
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Glenna
5 months ago
Definitely agree with LogUniform!
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Amie
5 months ago
I think Normal and LogUniform are solid choices!
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Beckie
5 months ago
I’m leaning towards Uniform and LogUniform as the right answers. I remember practicing with those in the context of Bayesian optimization.
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Gilma
5 months ago
LogUniform sounds familiar too, especially for parameters like learning_rate. I just can't recall if it's the best fit for this scenario.
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Alesia
5 months ago
I think Uniform could definitely be one of the options since it allows for a wide range of values. I feel like I've seen a similar question before.
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Lashawnda
6 months ago
I remember we discussed different distributions for hyperparameter tuning, but I'm not entirely sure if Normal is a good choice for learning_rate.
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Juan
6 months ago
Hmm, I'm a bit unsure here. I know RNNs can handle sequences, but I'm wondering if Convolutional Neural Networks (CNNs) might also work well for this kind of text-to-text translation problem. I'll have to think it through more carefully.
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Chauncey
6 months ago
Hmm, I'm not sure about Duo Multifactor Authentication. I'll have to think about that one a bit more.
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Rolland
6 months ago
I've got a good feeling about this one. The answer is definitely Business process outsourcing. That's the term that best describes the structure where the finance function is handled by an external party.
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