Creating pretrained network weights for downstream tasks

Also known as unsupervised transfer learning, this method is analogous to supervised transfer learning and naturally reaps the same benefits as described in the Transfer learning section in Chapter 8, Exploring Supervised Deep Learning. But as a recap, let’s go through an analogy. Imagine you’re a chef who has spent years learning how to cook a variety of dishes, from pasta and steak to desserts. One day, you’re asked to cook a new dish you’ve never tried before; let’s call it “Dish X.” Instead of starting from scratch, you use your prior knowledge and experience to simplify the process. You know how to chop vegetables, how to use the oven, and how to adjust the heat, so you don’t have to relearn all of these steps. You can focus your energy on learning the specific ingredients and techniques required for Dish X This is similar to how transfer learning works in machine learning...