Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Learning Hub

Conferences

Free Learning

Hands-On Deep Learning for IoT: Train neural network models to develop intelligent IoT applications

Dr. Mohammad Abdur Razzaque

Md. Rezaul Karim

€8.99 ~~€22.99~~

4 (1 Ratings)

eBook Jun 2019 308 pages 1st Edition

Dr. Mohammad Abdur Razzaque

Md. Rezaul Karim

€8.99 ~~€22.99~~

4 (1 Ratings)

eBook Jun 2019 308 pages 1st Edition

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

View table of contents

Preview Book

Download Code

Key benefits

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

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.

Who is this book 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.

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Product Details

Publication date : Jun 27, 2019

Length: 308 pages

Edition : 1st

Language : English

ISBN-13 : 9781789616064

Category :

Data

Languages :

Python

Concepts :

Deep Learning

Tools :

TensorFlow

Frequently bought together

Hands-On Deep Learning for IoT

Jun 2019 308 pages

4 (1)

eBook

€8.99 ~~€22.99~~

Hands-On Artificial Intelligence for Cybersecurity

Aug 2019 342 pages

4.4 (5)

eBook

€8.99 ~~€29.99~~

Hands-On Artificial Intelligence for IoT

Jan 2019 390 pages

5 (4)

eBook

€8.99 ~~€32.99~~

Total € 107.97

€28.99

€36.99

€41.99

Total € 107.97

14 Chapters

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

The End-to-End Life Cycle of the IoT

The E2E life cycle of the IoT

IoT application domains

The importance of analytics in IoT

The motivation to use DL in IoT data analytics

The key characteristics and requirements of IoT data

Summary

Reference

Deep Learning Architectures for IoT

A soft introduction to ML

ML tasks

Delving into DL

Artificial neural networks

Neural network architectures

DL frameworks and cloud platforms for IoT

Summary

Section 2: Hands-On Deep Learning Application Development for IoT

Image Recognition in IoT

IoT applications and image recognition

Use case one – image-based automated fault detection

Use case two – image-based smart solid waste separation

Transfer learning for image recognition in IoT

CNNs for image recognition in IoT applications

Collecting data for use case one

Collecting data for use case two

Audio/Speech/Voice Recognition in IoT

Speech/voice recognition for IoT

Use case one – voice-controlled smart light

Use case two – voice-controlled home access

DL for sound/audio recognition in IoT

CNNs and transfer learning for speech recognition in IoT applications

Indoor Localization in IoT

An overview of indoor localization

DL-based indoor localization for IoT

Example – Indoor localization with Wi-Fi fingerprinting

Deployment techniques

Summary

Physiological and Psychological State Detection in IoT

IoT-based human physiological and psychological state detection

Use case one – remote progress monitoring of physiotherapy

Use case two — IoT-based smart classroom

Deep learning for human activity and emotion detection in IoT

LSTM, CNNs, and transfer learning for HAR/FER in IoT applications

IoT Security

Security attacks in IoT and detections

Use case one: intelligent host intrusion detection in IoT

Use case two: traffic-based intelligent network intrusion detection in IoT

DL for IoT security incident detection

Section 3: Advanced Aspects and Analytics in IoT

Predictive Maintenance for IoT

Predictive maintenance for IoT

Example – PM for an aircraft gas turbine engine

DL for predicting RLU

FAQs

Summary

Deep Learning in Healthcare IoT

IoT in healthcare

Use case one – remote management of chronic disease

Use case two – IoT for acne detection and care

What's Next - Wrapping Up and Future Directions

What we have covered in this book?

Deployment challenges of DL solutions in resource-constrained IoT devices

Existing solutions to support DL in resource-constrained IoT devices

Potential future solutions

Summary

References

Other Books You May Enjoy

Leave a review - let other readers know what you think

Recommendations for you

Python Machine Learning By Example

Jul 2024 518 pages

4.9 (8)

eBook

€8.99 ~~€27.99~~

Unlocking Data with Generative AI and RAG

Sep 2024 346 pages

eBook

€8.99 ~~€23.99~~

Building LLM Powered Applications

May 2024 342 pages

4.2 (22)

eBook

€8.99 ~~€29.99~~

Python for Algorithmic Trading Cookbook

Aug 2024 404 pages

4.6 (15)

eBook

€8.99 ~~€35.99~~

Machine Learning with PyTorch and Scikit-Learn

Feb 2022 774 pages

4.4 (95)

eBook

€8.99 ~~€32.99~~

Artificial Intelligence Engines

Nov 2024 217 pages

eBook

€4.99 ~~€7.99~~

AI Product Manager's Handbook

Nov 2024 484 pages

eBook

€8.99 ~~€29.99~~

RAG-Driven Generative AI

Sep 2024 334 pages

4.5 (13)

eBook

€8.99 ~~€32.99~~

Hands-On Reinforcement Learning with Python

Jun 2018 318 pages

2.6 (18)

eBook

€8.99 ~~€23.99~~

LLM Engineer's Handbook

Oct 2024 522 pages

4.9 (15)

eBook

€8.99 ~~€43.99~~

Customer reviews

Rating distribution

(1 Ratings)

5 star 0%

4 star 100%

3 star 0%

2 star 0%

1 star 0%

Amazon Customer Sep 29, 2019

This is a very helpful book for the beginners in Internet Of Things. It helped me a lot in understanding the basics. This is a must have book for everyone who wants to learn IoT.

Amazon Verified review

People who bought this also bought

Machine Learning Engineering with Python

Aug 2023 462 pages

4.6 (36)

eBook

€8.99 ~~€29.99~~

Deep Learning with TensorFlow and Keras – 3rd edition

Oct 2022 698 pages

4.6 (45)

eBook

€8.99 ~~€29.99~~

Modern Generative AI with ChatGPT and OpenAI Models

May 2023 286 pages

4.2 (34)

eBook

€8.99 ~~€29.99~~

Generative AI with LangChain

Dec 2023 368 pages

4 (34)

eBook

€8.99 ~~€29.99~~

Causal Inference and Discovery in Python

May 2023 456 pages

4.5 (49)

eBook

€8.99 ~~€23.99~~

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).

See other products by Dr. Mohammad Abdur Razzaque

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.

See other products by Md. Rezaul Karim

FAQs

How do I buy and download an eBook?

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

You may make copies of your eBook for your own use onto any machine
You may not pass copies of the eBook on to anyone else

How can I make a purchase on your website?

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

Register on our website using your email address and the password.
Search for the title by name or ISBN using the search option.
Select the title you want to purchase.
Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title.
Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)

Where can I access support around an eBook?

If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
To view your account details or to download a new copy of the book go to www.packtpub.com/account
To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us

What eBook formats do Packt support?

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks?

You can get the information you need immediately
You can easily take them with you on a laptop
You can download them an unlimited number of times
You can print them out
They are copy-paste enabled
They are searchable
There is no password protection
They are lower price than print
They save resources and space

What is an eBook?

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.

Hands-On Deep Learning for IoT: Train neural network models to develop intelligent IoT applications

What do you get with eBook?