What is exactly we mean by transfer learning?
I know that it’s using a pre-trained model and its parameters such as weights and biases then we adapt the hyperparameters such as epochs and learning rates.
But can we use it for a totally different dataset? If not what is the benefit of using pre-trained models rather than reducing the training time?
Can we name all the CNN as transfer learning? Since it’s changing the information from pixels to matrix mat and still reserve the spacial and pattern relationship which is kind of strong transfer learning?