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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

Reinforcement Learning for IoT

Reinforcement learning (RL) is very different from both supervised and unsupervised learning. It's the way most living beings learn—interacting with the environment. In this chapter, we'll study different algorithms employed for RL. As you progress through the chapter, you'll do the following:

  • Learn what RL is and how it's different from supervised learning and unsupervised learning
  • Lear different elements of RL
  • Learn about some fascinating applications of RL in the real world
  • Understand the OpenAI interface for training RL agents
  • Learn about Q-learning and use it to train an RL agent
  • Learn about Deep Q-Networks and employ them to train an agent to play Atari
  • Learn about the policy gradient algorithm and use it to
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