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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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Toc

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

How it works...

In this recipe, we are using numpy for data manipulation, sklearn for the machine learning algorithm, and matplotlib for viewing the results. Next, we pull the tab-separated file into a Spark dataframe. In this step, we convert the data into a pandas DataFrame. Then we run the k-means algorithm with three clusters, which gives the chart as the output.

K-means is an algorithm that helps group data into clusters. K-means is a popular clustering algorithm for examining data without labels. K-means first randomly initializes cluster centroids. In our example, it had three cluster centroids. It then assigns the centroids to the nearest data points. Next, it moves each centroid to the spot that is in the middle of its respective cluster. It repeats these steps until it achieves an appropriate division of data points.

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