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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

HDFS

HDFS is a popular storage and access method for storing and retrieving data files for IoT solutions. The HDFS format can hold large amounts of data in a reliable and scalable manner. Its design is based on the Google File System (https://ai.google/research/pubs/pub51). HDFS splits individual files into fixed-size blocks that are stored on machines across the cluster. To ensure reliability, it replicates the file blocks and distributes them across the cluster; by default, the replication factor is 3. HDFS has two main architecture components:

The first, NodeName, stores the metadata for the entire filesystem, such as filenames, their permissions, and the location of each block of each file.
The second, DataNode (one or more), is where file blocks are stored. It performs Remote Procedure Calls (RPCs) using protobufs.

Note

RPC is a protocol that one program can use to request a service from a program located on another computer on a network without having to know the network's details. A...

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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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