Hands-On Meta Learning with Python

What this book covers

Chapter 1, Introduction to Meta Learning, helps us to understand what meta learning is and covers the different types of meta learning. We will also learn how meta learning uses few-shot learning by learning from a few data points. We will then see how to become familiar with gradient descent. Later in the chapter, we will see optimization as a model for the few shot learning setting. Chapter 2, Face and Audio Recognition Using Siamese Networks, starts by explaining what siamese networks are and how siamese networks are used in the one-shot learning setting. We will look at the architecture of a siamese network and some of the applications of a siamese network. Then, we will see how to use the siamese networks to build ...