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Deep Neuro-Fuzzy Systems with Python

With Case Studies and Applications from the Industry

Authors: Singh, Himanshu, Lone, Yunis Ahmad

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  • Explains deep neuro-fuzzy systems with applications and mathematical details
  • Implementations of all the applications using Python
  • Covers the recent applications of neuro fuzzy inference systems in industry
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eBook 22,99 €
price for Germany (gross)
  • ISBN 978-1-4842-5361-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 29,95 €
price for Germany (gross)
  • ISBN 978-1-4842-5360-1
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
About this book

Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python.

You’ll start by walking through the basics of fuzzy sets and relations, and how each member of the set has its own membership function values. You’ll also look at different architectures and models that have been developed, and how rules and reasoning have been defined to make the architectures possible. The book then provides a closer look at neural networks and related architectures, focusing on the various issues neural networks may encounter during training, and how different optimization methods can help you resolve them.

In the last section of the book you’ll examine the integrations of fuzzy logics and neural networks, the adaptive neuro fuzzy Inference systems, and various approximations related to the same. You’ll review different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by reviewing advanced neuro fuzzy models and applications. 

What You’ll Learn

  • Understand fuzzy logic, membership functions, fuzzy relations, and fuzzy inference
  • Review neural networks, back propagation, and optimization
  • Work with different architectures such as Takagi-Sugeno model, Hybrid model, genetic algorithms, and approximations
  • Apply Python implementations of deep neuro fuzzy system 

Who This book Is For 

Data scientists and software engineers with a basic understanding of Machine Learning who want to expand into the hybrid applications of deep learning and fuzzy logic.




About the authors

Himanshu Singh is currently a Consultant to Artificial Intelligence for ADP Inc. with over 5 years of experience in the AI industry, primarily in Computer Vision and Natural Language Processing. Himanshu has authored three books on Machine Learning. He has an MBA from Narsee Monjee Institute of Management Studies, and a postgraduate diploma in Applied Statistics. 

Yunis Ahmad Lone has over 22 years of experience in the IT industry, has been involved with Machine Learning for 10 years. Currently, Yunis is a PhD researcher at Trinity College, Dublin, Ireland. Yunis completed his Bachelors and Masters both from BITS Pilani, and worked on various leadership positions in MNCs like Tata Consultancy Services, Deloitte, and Fidelity Investments.

Table of contents (7 chapters)

Table of contents (7 chapters)
  • Introduction to Fuzzy Set Theory

    Pages 1-34

    Singh, Himanshu (et al.)

  • Fuzzy Rules and Reasoning

    Pages 35-92

    Singh, Himanshu (et al.)

  • Fuzzy Inference Systems

    Pages 93-127

    Singh, Himanshu (et al.)

  • Introduction to Machine Learning

    Pages 129-156

    Singh, Himanshu (et al.)

  • Artificial Neural Networks

    Pages 157-198

    Singh, Himanshu (et al.)

Buy this book

eBook 22,99 €
price for Germany (gross)
  • ISBN 978-1-4842-5361-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 29,95 €
price for Germany (gross)
  • ISBN 978-1-4842-5360-1
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Deep Neuro-Fuzzy Systems with Python
Book Subtitle
With Case Studies and Applications from the Industry
Authors
Copyright
2020
Publisher
Apress
Copyright Holder
Himanshu Singh, Yunis Ahmad Lone
eBook ISBN
978-1-4842-5361-8
DOI
10.1007/978-1-4842-5361-8
Softcover ISBN
978-1-4842-5360-1
Edition Number
1
Number of Pages
XV, 260
Number of Illustrations
143 b/w illustrations
Topics

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