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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

Multilayered perceptrons for regression and classification

In the last section, you learned about a single artificial neuron and used it to predict the energy output. If we compare it with the linear regression result of Chapter 3, Machine Learning for IoT, we can see that though the single neuron did a good job, it was not as good as linear regression. The single neuron architecture had an MSE value of 0.078 on the validation dataset as compared 0.01 of linear regression. Can we make it better, with maybe more epochs, or different learning rate, or perhaps more single neurons. Unfortunately not, single neurons can solve only linearly separable problems, for example, they can provide a solution only if there exists a straight line separating the classes/decision.

Note

The network with a single layer of neurons is called simple perceptron. The perceptron model was given by Rosenblatt in 1958 (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.335.3398&rep=rep1&type=pdf...

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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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