Hyperparameters

#deep-learning #interview

Hyperparameters are values that we need to fix based on the train and validation data.
Some of the common hyperparameters are,

  1. Number of neurons in the hidden layer
  2. Number of hidden layers
  3. Weight Initialization
  4. Learning Rate
  5. Number of Epochs
  6. Batch Size

Related Notes