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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

CSV format


Comma-separated value (CSV) files are the most popular formats for storing tabular data generated by IoT systems. In a .csv file, the values of the records are stored in plain-text rows, with each row containing the values of the fields separated by a separator. The separator is a comma by default but can be configured to be any other character. In this section, we will learn how to use data from CSV files with Python's csv, numpy, and pandas modules. We will use the household_power_consumption data file. The file can be downloaded from the following GitHub link: https://github.com/ahanse/machlearning/blob/master/household_power_consumption.csv. To access the data files, we define the following variables:

data_folder = '../../data/household_power_consumption' 
data_file = 'household_power_consumption.csv'

Generally, to quickly read the data from CSV files, use the Python csv module; however, if the data needs to be interpreted as a mix of date, and numeric data fields, it's better...

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