Hyperparameter Tuning of Deep Learning Algorithm

#artificialintelligence 

There is no hard and fast role towards importance of hyperparameters. Grid Method: Impose a grid on possible space of a hyperparameter and then go over each cell of grid one by one and evaluate your model against values from that cell. Grid method tends to vast resources in trying out parameter values which would not make sense at all. Random Sampling Method: In random method, we have high probability of finding good set of params quickly. Random sampling allows efficient search in hyperparameter space.