We have already briefly discussed the advantages of transfer learning, in Chapter 4, Transfer Learning Fundamentals. To recap, we get several benefits, such as improving the baseline performance, speeding up the overall model development and training time, and also getting an overall improved and superior model performance as compared to building a deep learning model from scratch. An important thing to remember here is that transfer learning as a domain existed long before deep learning and can also be applied to areas or problems that do not need deep learning.
Let's consider a real-world problem now, one which we will also be using throughout this chapter to illustrate our different deep learning models and leverage transfer learning on the same. One of the key requirements of deep learning, which you must have heard time and again, is that...
