You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace. You must configure a grid sampling method over the search space for the num_hidden_layers and batch_size hyperparameters. You need to identify the hyperparameters for the grid sampling. Which hyperparameter sampling approach should you use?

QuestionsCategory: DP-100You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace. You must configure a grid sampling method over the search space for the num_hidden_layers and batch_size hyperparameters. You need to identify the hyperparameters for the grid sampling. Which hyperparameter sampling approach should you use?
Admin Staff asked 4 months ago
You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace.
You must configure a grid sampling method over the search space for the num_hidden_layers and batch_size hyperparameters.
You need to identify the hyperparameters for the grid sampling.
Which hyperparameter sampling approach should you use?

A. uniform

B. qlognormal

C. choice

D. normal








 

Suggested Answer: B



This question is in DP-100 Exam
For getting Microsoft Azure Data Scientist Associate Certificate


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