In a hyperparameter search, whether a single model is trained or a lot of models are trained in parallel is largely determined by?

In a hyperparameter search, whether a single model is trained or a lot of models are trained in parallel is largely determined by?
A . The number of hyperparameters you have to tune.
B . The presence of local minima in your neural network.
C . The amount of computational power you can access.
D . Whether you use batch or mini-batch optimization.

View Answer

Answer: C

Explanation:

Reference: https://github.com/Kulbear/deep-learning-coursera/blob/master/Improving%20Deep%20Neural %20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%203%20Quiz%20-%20Hyperparameter%20tuning%2C%20Batch%20Normalization%2C%20Programming%20Frameworks.md