Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
size, the number of hidden layers, and then the learning rate decay. Now, suppose we have two hyperparameters. We sample the points in a grid and then systematically explore these values. Consider a five-by-five grid: We check all 25 values and pick whichever hyperparameter works best. Instead of