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Hands-On Deep Learning for IoT

You're reading from   Hands-On Deep Learning for IoT Train neural network models to develop intelligent IoT applications

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781789616132
Length 308 pages
Edition 1st Edition
Languages
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Authors (3):
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Aditya Trivedi Aditya Trivedi
Author Profile Icon Aditya Trivedi
Aditya Trivedi
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Dr. Mohammad Abdur Razzaque Dr. Mohammad Abdur Razzaque
Author Profile Icon Dr. Mohammad Abdur Razzaque
Dr. Mohammad Abdur Razzaque
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: IoT Ecosystems, Deep Learning Techniques, and Frameworks FREE CHAPTER
2. The End-to-End Life Cycle of the IoT 3. Deep Learning Architectures for IoT 4. Section 2: Hands-On Deep Learning Application Development for IoT
5. Image Recognition in IoT 6. Audio/Speech/Voice Recognition in IoT 7. Indoor Localization in IoT 8. Physiological and Psychological State Detection in IoT 9. IoT Security 10. Section 3: Advanced Aspects and Analytics in IoT
11. Predictive Maintenance for IoT 12. Deep Learning in Healthcare IoT 13. What's Next - Wrapping Up and Future Directions 14. Other Books You May Enjoy

Artificial neural networks

ANNs, which are inspired by how a human brain works, form the core of DL and its true realization. Today's revolution around DL would not have been possible without ANNs. Thus, to understand DL, we need to understand how neural networks work.

ANN and the human brain

ANNs represent one aspect of the human nervous system, and how the nervous system consists of a number of neurons that communicate with each other using axons. The receptors receive the stimuli either internally or from the external world. Then, they pass this information to the biological neurons for further processing. There are a number of dendrites, in addition to another long extension called the axon. Toward the axon's...

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