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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

Conclusions and Other Approaches

In this book, we have learned about various forms of architectures for deep learning, and various techniques and methods, ranging from manual feature extraction to the variational Bayesian framework. One-shot learning is a particularly active field of research as it focuses on building a type of machine consciousness more closely based on human neural abilities. With advancements made in the deep learning community over the past 5 years, we can at least say that we are on the path to developing a machine that can learn multiple tasks at once, just as a human can. In this chapter, we will see what other alternatives there are to one-shot learning, and discuss other approaches that haven't been explored in depth in this book.

The following topics will be covered:

  • Recent advancements
  • Related fields
  • Applications
...
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