Grid search vs random search algorithms
Grid search is used for training the network for every combination
by using the two sets of hyperparameters
that are learning rate,
and the number of layers.
After that, it examines the model using Cross-Validation techniques.
Random Search randomly samples the search space and
examines the sets from a particular probability distribution.
For example, rather than checking all 10,000 samples,
randomly selected 100 parameters can be examined.