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Hands-On Artificial Intelligence for IoT

You're reading from   Hands-On Artificial Intelligence for IoT Expert machine learning and deep learning techniques for developing smarter IoT systems

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788836067
Length 390 pages
Edition 2nd Edition
Languages
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Author (1):
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Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
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Table of Contents (14) Chapters Close

Preface 1. Principles and Foundations of IoT and AI 2. Data Access and Distributed Processing for IoT FREE CHAPTER 3. Machine Learning for IoT 4. Deep Learning for IoT 5. Genetic Algorithms for IoT 6. Reinforcement Learning for IoT 7. Generative Models for IoT 8. Distributed AI for IoT 9. Personal and Home IoT 10. AI for the Industrial IoT 11. AI for Smart Cities IoT 12. Combining It All Together 13. Other Books You May Enjoy

ML and IoT


ML, a subset of artificial intelligence, aims to build computer programs with an ability to automatically learn and improve from experience without being explicitly programmed. In this age of big data, with data being generated at break-neck speed, it isn't humanly possible to go through all of the data and understand it manually. According to an estimate by Cisco, a leading company in the field of IT and networking, IoT will generate 400 zettabytes of data a year by 2018. This suggests that we need to look into automatic means of understanding this enormous data, and this is where ML comes in.

Note

The complete Cisco report, released on February 1, 2018, can be accessed at https://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.html. It forecasts data traffic and cloud service trends in light of the amalgamation of IoT, robotics, AI, and telecommunication. 

 

Every year, Gartner, a research and advisory firm, releases a graphical...

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