Beginners guide to transfer learning on Google Colab

Mammoth quantities of pristine data are one of the most valuable resources in these times, which is the potential source of huge revenue thanks to advances in deep learning and associated hardware that's needed to speed up those innumerable matrix multiplications. What if we don't have a lot of data and procuring more isn't feasible? Or we lack the expensive hardware that's imperative for training very deep networks? Both can be solved by using the concept of transfer learning, which we'll soon find out is something we are unconsciously familiar with. Transfer learning is a supervised learning method that aids construction of new models using pre-trained weights of previously constructed and fine-tuned models.