Transfer learning make use of the knowledge gained while solving one problem and applying it to a different but related problem.
For example, knowledge gained while learning to recognize cars can be used to some extent to recognize trucks.
Pre-Training
When we train the network on a large dataset(for example: ImageNet) , we train all the parameters of the neural network and therefore the model is learned. It may take hours on your GPU.