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Learning AWS IoT

You're reading from   Learning AWS IoT Effectively manage connected devices on the AWS cloud using services such as AWS Greengrass, AWS button, predictive analytics and machine learning

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396110
Length 278 pages
Edition 1st Edition
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Author (1):
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Agus Kurniawan Agus Kurniawan
Author Profile Icon Agus Kurniawan
Agus Kurniawan
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with AWS IoT 2. Connecting IoT Devices to AWS IoT Platform FREE CHAPTER 3. Optimizing IoT Computing Using AWS Greengrass 4. Building Local AWS Lambda with AWS Greengrass 5. Expanding IoT Capabilities with AWS IoT Button 6. Visualizing AWS IoT Data 7. Building Predictive Analytics for AWS IoT 8. Securing AWS IoT 9. Other Books You May Enjoy

Make predictive analytics for IoT data


Predictive analytics is a method to make prediction for an unknown event. In the context of IoT, we can develop predictive analytics to make a decision-based streaming sensor data. This is a part of machine learning study. In general, we can make predictive analytics using a diagram that is shown as follows:

Defining business problems is the first step to develop predictive analytics. Some problems probably need experts to make clear those problems. For instance, economics, biology, and volcanology. 

We also should prepare data in order to develop a model. This data should have high impact factors on the model.  When we develop a model, we also perform some steps such as defining targets, extracting derived features from data, fitting the model, and evaluating the model. In a real project, we probably make some iterations to ensure the corrected model.

After we developed the model, we can deploy the model into our system. This could be deployed in web...

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