Book Image

Hands-On Meta Learning with Python

By : Sudharsan Ravichandiran
Book Image

Hands-On Meta Learning with Python

By: Sudharsan Ravichandiran

Overview of this book

Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models.
Table of Contents (17 chapters)
Title Page
About Packt

Chapter 3. Prototypical Networks and Their Variants

In the last chapter, we learned what siamese networks are and how they are used to perform few-shot learning tasks. We also explored how to use siamese networks for performing face and audio recognition. In this chapter, we will look at another interesting few-shot learning algorithm called a prototypical network, which has the ability to generalize even to the class that is not present in a training set. We will start off with understanding what prototypical networks are, after which we will see how to perform a classification task in an omniglot dataset using prototypical network. We will then see different variants of prototypical networks, such as Gaussian prototypical networks and semi-prototypical networks.

In this chapter, you will learn about the following:

  • Prototypical networks
  • The algorithm of prototypical networks
  • Classification using prototypical networks
  • Gaussian prototypical networks
  • The Gaussian prototypical network algorithm
  • Semi...