Machine Learning Algorithms and Applications

Mettu Srinivas, G. Sucharitha, Anjanna Matta, Mettu Srinivas, G. Sucharitha, Anjanna Matta

• Publisher: Wiley-Scrivener
• Year: 2021
• Print ISBN: 9781119768852
• eBook ISBN: 9781119769248
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms.

The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.

Part 1
MACHINE LEARNING FOR INDUSTRIAL APPLICATIONS

1
A Learning-Based Visualization Application for Air Quality Evaluation During COVID-19 Pandemic in Open Data Centric Services

Priyank Jain* and Gagandeep Kaur^†

Dept. of CSE & IT, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

Abstract

Air pollution has become a major concern in many developing countries. There are various factors that affect the quality of air. Some of them are Nitrogen Dioxide (NO₂), Ozone (O₃), Particulate Matter 10 (PM₁₀), Particulate Matter 2.5 (PM_2.5), Sulfur Dioxide (SO₂), and Carbon Monoxide (CO). The Government of India under the Open Data Initiative provides data related to air pollution. Interpretation of this data requires analysis, visualization, and prediction. This study proposes machine learning and visualization techniques for air pollution. Both supervised and unsupervised learning techniques have been used for prediction and analysis of air quality at major places in India. The data used in this research contains the presence of six major air pollutants in a given area. The work has been extended to study the impact of lockdown on air pollution in Indian cities as well.

Keywords: Open Data, JSON API, OpenAQ, clustering, SVM, LSTM, prediction, Heat Map visualizations

1.1 Introduction

1.1.1 Open Government Data Initiative

These days, Open Government Data (OGD) is gaining momentum in providing sharing of knowledge by making public data and information of governmental bodies freely available to private citizens in system processable formats so as to reuse it for mutual benefits. OGD is a global movement and has its roots in the initiative started in 2009 by the US President as a Memorandum on Transparency and Open Government providing transparency in government projects and collaborations through sharing of data by public administration and industry to private citizens. Indian Government also has joined this initiative and provides free access to the data for development of applications, etc., so as to be able to reuse the information for mutual growth of industry and government. Open Data is the raw data made available by governments, industry, as well as NGOs, scientific institutions, and educational organizations and as such is not an individual’s property.

The growth in the field of Open Data surely asks for new tools and techniques that can support it. Digital transformation needs companies to look out for new tools and techniques so as to be able to support the increasing need for faster delivery of services at large numbers of delivery points. Technologies like SaaS, mobile, and Internet of Things are gaining grounds in providing increase in endpoints and thus enabling the success of Open Data Initiative.

1.1.2 Air Quality

A report, State of Global Air 2017, by Institute for Health Metrics published recently [1] stated that, in the year 2015, there have been 1,090,400 deaths in India only due to an increase in PM_2.5. High concentration of PM_2.5 in the air is majorly caused by burning of petroleum fuels, household fuels, wooden fuels, agricultural fires, and industry related pollutants and contaminants. In 2015, India and Bangladesh came next to North African and Middle East countries in terms of places with high concentration of PM_2.5 in air.

The report compares the ambient concentrations to the air quality guidelines established by the WHO in 2005. Based on the report by WHO, in the year 2015, 92% of the world’s population and 86% of Indian population lived in unsafe areas exceeding safe limits. It is therefore need of the hour to develop tools that can provide better forecasting and easy understanding of the surrounding environment to naive users with lowest cost possible. Air Quality Index (AQI) is a commonly used index by agencies to provide informa...

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright
• Acknowledgments
• Preface
• Part 1 MACHINE LEARNING FOR INDUSTRIAL APPLICATIONS
• Part 2 MACHINE LEARNING FOR HEALTHCARE SYSTEMS
• Part 3 MACHINE LEARNING FOR SECURITY SYSTEMS
• Part 4 MACHINE LEARNING FOR CLASSIFICATION AND INFORMATION RETRIEVAL SYSTEMS
• Index
• End User License Agreement