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Exam DP-100 topic 3 question 130 discussion

Actual exam question from Microsoft's DP-100
Question #: 130
Topic #: 3
[All DP-100 Questions]

HOTSPOT
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You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace. You add code that imports all relevant Python libraries.

You must configure Bayesian sampling over the search space for the num_hidden_layers and batch_size hyperparameters.

You need to complete the following Python code to configure Bayesian sampling.

Which code segments should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Suggested Answer:
by Nghia1 at June 6, 2023, 8:01 p.m.

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haby
Highly Voted 1 year, 4 months ago
correct for me. range(16,128,16) means select all numbers from 16 to 128 with 16 intervals. for i in range(16,128,16) : print(i) output : 16 32 ... Not uniform since uniform should only have 2 parameters:(min_num, max_num) ref : https://learn.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.hyperdrive.parameter_expressions?view=azure-ml-py
upvoted 5 times
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jl420
Most Recent 5 months, 2 weeks ago
this question is broken
upvoted 1 times
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Nghia1
1 year, 10 months ago
correct https://learn.microsoft.com/en-us/training/modules/tune-hyperparameters-with-azure-machine-learning/3-sampling
upvoted 3 times
orionduo
1 year, 7 months ago
your link gives the answer choice & uniform but you said the anwser is correct weird
upvoted 1 times
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Gosku666
1 year, 10 months ago
Regarding link that you've added should be: choice and uniform for Bayesian sampling: "You can only use Bayesian sampling with choice, uniform, and quniform parameter expressions, and you can't combine it with an early-termination policy."
upvoted 1 times
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