Skip to main content
Have a personal or library account? Click to login
Hands-On Deep Learning for IoT Cover

Hands-On Deep Learning for IoT

Train neural network models to develop intelligent IoT applications

Publisher:Packt Publishing Limited
By: Dr. Mohammad Abdur Razzaque Razzaque and  Md. Rezaul Karim  
Paid access
|Jan 2019
Product purchase options
Description

Implement popular deep learning techniques to make your IoT applications smarter

Key Features

  • Understand how deep learning facilitates fast and accurate analytics in IoT
  • Build intelligent voice and speech recognition apps in TensorFlow and Chainer
  • Analyze IoT data for making automated decisions and efficient predictions

Book Description

Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale.
Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT.
You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN).
You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced.
By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making.

What you will learn

  • Get acquainted with different neural network architectures and their suitability in IoT
  • Understand how deep learning can improve the predictive power in your IoT solutions
  • Capture and process streaming data for predictive maintenance
  • Select optimal frameworks for image recognition and indoor localization
  • Analyze voice data for speech recognition in IoT applications
  • Develop deep learning-based IoT solutions for healthcare
  • Enhance security in your IoT solutions
  • Visualize analyzed data to uncover insights and perform accurate predictions

Who this book is for

If you’re an IoT developer, data scientist, or deep learning enthusiast who wants to apply deep learning techniques to build smart IoT applications, this book is for you. Familiarity with machine learning, a basic understanding of the IoT concepts, and some experience in Python programming will help you get the most out of this book.

Table of Contents

  1. End-to-End Life Cycle of IoT
  2. Deep Learning Architectures for IoT
  3. Image Recognition in IoT
  4. Audio/Speech/Voice Recognition in IoT
  5. Indoor localization in IoT
  6. Physiological and Psychological State Detection in IoT
  7. Security and privacy for IoT
  8. Predictive Maintenance for IoT
  9. Deep learning in Healthcare IoT
  10. What
https://github.com/packtpublishing/hands-on-deep-learning-for-iot
PDF ISBN: 978-1-78961-606-4
Publisher: Packt Publishing Limited
Publication date: 2019
Language: English
Pages: 308
Related subjects:
Computer sciences,
Computer sciences, other

People also read

Hands-On Artificial Intelligence for IoT
Book

Hands-On Artificial Intelligence for IoT

Amita Kapoor
​Hands-On Artificial Intelligence for IoT
Book

​Hands-On Artificial Intelligence for IoT

Dr. Amita Kapoor
Artificial Intelligence for IoT Cookbook
Book

Artificial Intelligence for IoT Cookbook

Michael Roshak
Deep Learning for Beginners
Book

Deep Learning for Beginners

Dr. Pablo Rivas, Dr. Pablo Rivas
Deep Learning By Example
Book

Deep Learning By Example

Ahmed Menshawy
Deep Learning Essentials
Book

Deep Learning Essentials

Wei Di, Jianing Wei, Anurag Bhardwaj
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
Book

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

Anubhav Singh, Rimjhim Bhadani
The Deep Learning Workshop
Book
Coming soon

The Deep Learning Workshop

Mirza Rahim Baig Baig, Thomas Joseph, Nipun Sadvilkar Sadvilkar
Applied Deep Learning
Book

Applied Deep Learning

Dr. Rajkumar Tekchandani, Dr. Neeraj Kumar
Essentials of Deep Learning and AI
Book

Essentials of Deep Learning and AI

Shashidhar Soppin, Dr. Manjunath Ramachandra, B N Chandrashekar