Non-Fiction Books:

Machine Learning Paradigm for Internet of Things Applications

Click to share your rating 0 ratings (0.0/5.0 average) Thanks for your vote!


Machine Learning Paradigm for Internet of Things Applications

or 4 payments of $100.25 with Learn more


Pre-order to reserve stock from our first shipment. Your credit card will not be charged until your order is ready to ship.

Dispatch date to be confirmed
Free Delivery with Primate
Join Now or upgrade at checkout
Pre-order Price Guarantee

If you pre-order an item and the price drops before the release date, you'll pay the lowest price. This happens automatically when you pre-order and pay by credit card or pickup.

If paying by PayPal, Afterpay, POLi, Online EFTPOS or internet banking, and the price drops after you have paid, you can ask for the difference to be refunded. Find out more

If Mighty Ape's price changes before release, you'll pay the lowest price.


This product will be released on

Delivering to:

It should arrive:

  • 11-12 April using standard courier service


The aim of the book is to explore the benefits of deploying Machine Learning (ML)in Internet of Things (IoT) environment. As a growing number of internet-connected sensors are built into cars, planes, trains and buildings, businesses are amassing vast amounts of data. Tapping into that data to extract useful information is a challenge that's starting to be met using the pattern-matching abilities of machine learning (ML) -- a subset of the field of artificial intelligence (AI). In order to provide smarter environment, their needs to be implemented IoT with machine learning. Machine learning will allow these smart devices to be smarter in a literal sense. It can analyze the data generated by the connected devices and get an insight into human's behavioral pattern. Hence, it would not be wrong to say that if the IoT is the digital nervous system, then ML acts as its medulla oblongata. This book provides the state-of-the-art applications of Machine Learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store 'contextualized marketing' and intelligent transportation systems. Readers will gain an insight into the integration of Machine Learning with IoT in various application domains.
Release date NZ
April 10th, 2022
  • Professional & Vocational
  • Edited by Deepali Gupta
  • Edited by G. R. Kanagachidambaresan
  • Edited by R. Maheswar
  • Edited by Sachin Ahuja
  • Edited by Shalli Rani
Country of Publication
United States
John Wiley & Sons Inc
Product ID

Customer previews

Nobody has previewed this product yet. You could be the first!

Write a Preview

Help & options

Filed under...