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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: * learning_rate: any value between 0.001 and 0.1 * batch_size: 16, 32, or 64 You need to configure the search space for the Hyperdrive experiment. Which two parameter expressions should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Correct Answer: B,D
B: Continuous hyperparameters are specified as a distribution over a continuous range of values. Supported distributions include: uniform(low, high) - Returns a value uniformly distributed between low and high D: Discrete hyperparameters are specified as a choice among discrete values. choice can be: one or more comma-separated values a range object any arbitrary list object Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters