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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

Logistic regression with the IoMT 

In this recipe, we're going to talk about using logistic regression to classify data from mammography machines. Recently, the IoMT has expanded greatly. Many devices are being worn by patients when they go home from their doctor, providing an in-home medical monitoring solution, while others are in hospitals, giving the doctors additional feedback on medical tests being run. In many cases, machine learning algorithms are able to spot diseases and issues that doctors may miss, or give them additional recommendations. In this recipe, we are going to work with a breast cancer dataset and determine whether a mammogram record is malignant or benign.

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