Hello, everyone
I am doing project whose data has several hundred variables (many of them are categorical)
and the model is binary classification
I am using deep learning with Pytorch
In this case, I want to know


how many hidden layers should I use?


how many nodes should I use for each hidden layer?


Is there any general theory or generally accepted methods to do these? I really want to know.
Thank you in advance and have a nice day!!!