Hands-On Meta Learning with Python

Sudharsan Ravichandiran

Digital

Available

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

   

What will you learn from this book

  • Understand the basics of meta learning methods, algorithms, and types
  • Build voice and face recognition models using a siamese network
  • Learn the prototypical network along with its variants
  • Build relation networks and matching networks from scratch
  • Implement MAML and Reptile algorithms from scratch in Python
  • Work through imitation learning and adversarial meta learning
  • Explore task agnostic meta learning and deep meta learning
Language English
ISBN-13 9781789537024
No of pages 226
Book Publisher Packt Publishing
Published Date 31 Dec 2018

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