Having set the context and basics of ML and deep learning in Chapter 1 to Chapter 3 of the book, this chapter began the second phase of building the foundations of transfer learning. Before diving into actual use cases, it is imperative that we formalize our understanding of transfer learning and learn about different techniques and research, and the challenges associated with it. Throughout this chapter, we have presented the fundamentals behind the concept of transfer learning, how it has evolved over the years, and why it was required in the first place.
We began by understanding transfer learning in the broader context of learning algorithms and their associated advantages. We then discussed various strategies for understanding, applying, and categorizing transfer learning methods. Transfer learning in the context of deep learning was the next topic discussed, to...
