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 2. Face and Audio Recognition Using Siamese Networks

In the last chapter, we learned about what meta learning is and different types of meta learning techniques. We also saw how to learn gradient descent by gradient descent and optimization as a model for few-shot learning. In this chapter, we will learn one of the most commonly used metric-based one-shot learning algorithms called siamese networks. We will see how siamese networks learn from very few data points and how they are used to solve the low data problem. After that we will explore the architecture of siamese networks in detail and we will see some of the applications of siamese networks. At the end of this chapter, we will learn how to build face and audio recognition models using siamese networks.

In this chapter, you will learn the following:

  • What are siamese networks?
  • Architecture of siamese networks
  • Applications of siamese networks
  • Face recognition using siamese networks
  • Building an audio recognition model using siamese...