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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

Preface 1. Section 1: One-shot Learning Introduction
2. Introduction to One-shot Learning FREE CHAPTER 3. Section 2: Deep Learning Architectures
4. Metrics-Based Methods 5. Model-Based Methods 6. Optimization-Based Methods 7. Section 3: Other Methods and Conclusion
8. Generative Modeling-Based Methods 9. Conclusions and Other Approaches 10. Other Books You May Enjoy

Summary

Deep learning has revolutionized the field of data science and it is still making progress, but there are still major industries that are yet to experience all of the advantages of deep learning, such as the medical and manufacturing industries. The zenith of human achievement will be to create a machine that can learn as humans do and that can become an expert in the same way humans can. Successful deep learning, though, usually comes with the prerequisite of having very large datasets to work from. Fortunately, this book focuses on architectures that can do away with this prerequisite.

In this chapter, we learned about the human brain and how the structure of an artificial neural network is close to the structure of our brain. We introduced the basic concepts of machine learning and deep learning, along with their challenges. We also discussed one-shot learning and its...

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Hands-On One-shot Learning with Python
Published in: Apr 2020
Publisher: Packt
ISBN-13: 9781838825461
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