I am using CNN for a binary classification problem and need to use Bayesian optimization to tune parameters like learning rate, number of hidden layers, optimizers, etc
I have built my model with fixed learning rate and number of epochs and Adam optimizer. Can you please give me some guidance on where to go from here in order to have Bayesian optimization implemented for tuning these parameters? And how would I deal with my 3 data sets (training, validation and test)?
I will really appreciate your help.
Thanks.