I would like to know your approaches for selecting the best hyperparameters for DNN models such as:

  • Number of epochs
  • Choice of optimizer
  • Varying the regularization method
  • Choice of activation function
  • Number of layers and number of neurons in each layer
  • Learning rate decay methods
  • Mini-batch size
  • Weight initialization methods

I need to specially know about tuning "Number of layers and number of neurons in each layer"

You can suggest papers, books or any other reliable reference.

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