Designing and Implementing a Data Science Solution on Azure — Question 16

You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.
You must use Hyperdrive to try combinations of the following hyperparameter values. You must not apply an early termination policy.
✑ learning_rate: any value between 0.001 and 0.1
✑ batch_size: 16, 32, or 64
You need to configure the sampling method for the Hyperdrive experiment.
Which two sampling methods can you use? Each correct answer is a complete solution.
NOTE: Each correct selection is worth one point.

Answer options

Correct answer: C, D

Explanation

The correct answers are C (Bayesian sampling) and D (Random sampling) because these methods allow for effective exploration of the hyperparameter space without early termination. Option A (No sampling) does not facilitate the exploration of combinations, while option B (Grid sampling) is not applicable due to the specified parameter constraints.