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Artificial Intelligence for IoT Cookbook

You're reading from   Artificial Intelligence for IoT Cookbook Over 70 recipes for building AI solutions for smart homes, industrial IoT, and smart cities

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838981983
Length 260 pages
Edition 1st Edition
Languages
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Author (1):
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Michael Roshak Michael Roshak
Author Profile Icon Michael Roshak
Michael Roshak
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Table of Contents (11) Chapters Close

Preface 1. Setting Up the IoT and AI Environment 2. Handling Data FREE CHAPTER 3. Machine Learning for IoT 4. Deep Learning for Predictive Maintenance 5. Anomaly Detection 6. Computer Vision 7. NLP and Bots for Self-Ordering Kiosks 8. Optimizing with Microcontrollers and Pipelines 9. Deploying to the Edge 10. About Packt

To get the most out of this book

Readers should have a basic understanding of software development. This book uses the Python, C, Java languages. A basic understanding of how to install libraries and packages in these languages as well as basic coding concepts such as arrays and loops will be helpful. A few websites that can help you brush up on the basics of different languages are:

To get the most out of this book a basic understanding of machine learning principles will be beneficial. The hardware used in this book are off the shelf sensors and common IoT development kits and can be purchased from sites such as Adafruit.com and Amazon.com. Most of the code is portable across devices. Device code written in Python can be easily ported to a variety of microprocessors such as a Raspberry Pi, Nvidia Jetson, Lotte Panda, or sometimes even a PC. While code written in C can be ported to a variety of microcontrollers such as the ESP32, ESP8266, and Arduino. Code written in Java can be ported to any android device such as a tablet or phone. 

This book uses Databricks for some of the experiments. Databricks has a free version at https://community.cloud.databricks.com.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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