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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

Introducing H2O.ai

H2O is a fast, scalable ML and deep learning framework developed by H2O.ai, released under the open source Apache license. According to the company-provided details, more than 9,000 organizations and 80,000+ data scientists use H2O for their ML/deep learning needs. It uses in-memory compression, which allows it to handle a large amount of data in memory, even with a small cluster of machines. It has an interface for R, Python, Java, Scala, and JavaScript, and even has a built-in web interface. H2O can run in standalone mode, and on Hadoop or Spark cluster.

H2O includes a large number of ML algorithms like generalized linear modeling, Naive Bayes, random forest, gradient boosting, and deep learning algorithms. The best part of H2O is that one can build thousands of models, compare the results, and even do hyperparameter tuning with a few lines of codes. H2O also has better data preprocessing tools.

H2O requires Java, so, ensure that Java is installed on your system. You...

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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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