Hands-On Deep Learning for IoT

5 (2 reviews total)
By Dr. Mohammad Abdur Razzaque , Md. Rezaul Karim
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  1. Section 1: IoT Ecosystems, Deep Learning Techniques, and Frameworks

About this book

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.

Publication date:
June 2019
Publisher
Packt
Pages
308
ISBN
9781789616132

 

Section 1: IoT Ecosystems, Deep Learning Techniques, and Frameworks

In this section, we will have an overview of IoT ecosystems, the key characteristics of IoT data (that is, real-time big data). We explain why analytics is necessary for data and why deep learning (DL) is important for analysis. We will also look into various techniques, their models and architectures, and their suitability in the IoT applications domain.

The following chapters are included in this section:

About the Authors

  • Dr. Mohammad Abdur Razzaque

    Dr. Mohammad Abdur Razzaque is a senior lecturer in the School of Computing and Digital Technologies, Teesside University, UK. He has more than 14 years of research and development and teaching experience on distributed systems (Internet of Things, P2P networking, and cloud computing) as well as experience in cybersecurity. He is an expert in end-to-end (sensors-to-cloud) IoT solutions. He offers consultancy in the areas of IoT solutions and the use of machine learning techniques in businesses. He has successfully published more than 65 research papers in these areas. He holds a PhD in distributed systems (P2P wireless sensor networks, mobile ad hoc networks) from the School of Computer Science and Informatics, UCD, Dublin (2008).

    Browse publications by this author
  • Md. Rezaul Karim

    Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

    Browse publications by this author

Latest Reviews

(2 reviews total)
Great books at affordable prices. Topics in Packt books are often current and of practical value.
I just started and this book is helful

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