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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 FREE CHAPTER 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 13. Other Books You May Enjoy

Deep Learning for IoT

In the last chapter, we learned about different machine learning (ML) algorithms. The focus of this chapter is neural networks based on multiple layered models, also known as deep learning models. They have become a buzzword in the last few years and an absolute favorite of investors in the field of artificial-intelligence-based startups. Achieving above human level accuracy in the task of object detection and defeating the world's Dan Nine Go master are some of the feats possible by deep learning (DL). In this chapter and a few subsequent chapters, we will learn about the different DL models and how to use DL on our IoT generated data. In this chapter, we will start with a glimpse into the journey of DL, and learn about four popular models, the multilayered perceptron (MLP), the convolutional neural network (CNN), recurrent neural network (RNN), and...

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