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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 FREE CHAPTER 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 13. Other Books You May Enjoy

Prediction using linear regression


Aaron, a friend of mine, is a little sloppy with money and is never able to estimate how much his monthly credit card bill will be. Can we do something to help him? Well, yes, linear regression can help us to predict a monthly credit card bill if we have sufficient data. Thanks to the digital economy, all of his monetary transactions for the last five years are available online. We extracted his monthly expenditure on groceries, stationery, and travel and his monthly income. Linear regression helped not only in predicting his monthly credit card bill, it also gave an insight into which factor was most responsible for his spending.

This was just one example; linear regression can be used in many similar tasks. In this section, we'll learn how we can perform linear regression on our data.

Linear regression is a supervised learning task. It's one of the most basic, simple, and extensively used ML techniques for prediction. The goal of regression is to find a...

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