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Hands-On Artificial Intelligence for IoT - Second Edition

You're reading from Hands-On Artificial Intelligence for IoT - Second Edition

Product type Book

Published in Jan 2019

Publisher Packt

ISBN-13 9781788836067

Pages 390 pages

Edition 2nd Edition

Languages

Concepts

Artificial Intelligence

Author (1):

Amita Kapoor

Table of Contents (20) Chapters

Title Page

Copyright and Credits

Dedication

About Packt

Contributors

Preface

1. Principles and Foundations of IoT and AI

2. Data Access and Distributed Processing for IoT

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

1. Other Books You May Enjoy

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Index

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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Authors (1)

Amita Kapoor

Amita Kapoor is an accomplished AI consultant and educator, with over 25 years of experience. She has received international recognition for her work, including the DAAD fellowship and the Intel Developer Mesh AI Innovator Award. She is a highly respected scholar in her field, with over 100 research papers and several best-selling books on deep learning and AI. After teaching for 25 years at the University of Delhi, Amita took early retirement and turned her focus to democratizing AI education. She currently serves as a member of the Board of Directors for the non-profit Neuromatch Academy, fostering greater accessibility to knowledge and resources in the field. Following her retirement, Amita also founded NePeur, a company that provides data analytics and AI consultancy services. In addition, she shares her expertise with a global audience by teaching online classes on data science and AI at the University of Oxford.

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