Transfer Learning for Deep Learning: Pre-trained models to save training time and cost

Training a neural network has been posing problems for researchers and developers for a long time. There are basically two major problems that arise during the development of DL based solution which are the astronomical costs of training, and the time required to train the network. Since training a neural network includes numerous matrix operations and demands a high computational capability, the cost of operation will escalate if one needs to perform a similar process again for another model. Also, the time to train them escalates at an exponential rate as the networks get deeper and complicated. Using GPUs is one effective way to speed up the process.