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Hands-On One-shot Learning with Python

You're reading from   Hands-On One-shot Learning with Python Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838825461
Length 156 pages
Edition 1st Edition
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Authors (2):
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Ankush Garg Ankush Garg
Author Profile Icon Ankush Garg
Ankush Garg
Shruti Jadon Shruti Jadon
Author Profile Icon Shruti Jadon
Shruti Jadon
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Toc

Table of Contents (11) Chapters Close

Section 2: Deep Learning Architectures

One-shot learning has been an active field of research for many scientists who are trying to find a cognitive machine that is as close as possible to humans in terms of learning. As there are various theories about how humans do one-shot learning, we have a lot of different deep learning methods that we can use to solve it. This section of the book will focus on metrics-based, model-based, and optimization-based deep learning architectures to tackle one-shot learning problems, along with their implementations.

This section comprises the following chapters:

  • Chapter 2, Metrics-Based Methods
  • Chapter 3, Model-Based Methods
  • Chapter 4, Optimization-Based Methods
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