Air Quality Prediction using Machine Learning

Author(s)	B.Raviteja, P.Tejaswini, U.Swetha Reddy
Country	India
Abstract	Air quality prediction using machine learning is a project that aims to provide accurate and reliable predictions of air quality in different regions. The project leverages advanced machine learning algorithms to analyze historical data on air quality and predict air quality index. By accurately predicting air quality levels, the project can help individuals and authorities take preventive measures to reduce exposure to pollutants and improve public health. The project utilizes various tools and technologies, including Python and Scikit-Learn to develop a robust and reliable system. Overall, this project has significant potential to positively impact public health and the environment, improving air quality and reducing the negative effects of pollution.
Keywords	KNN, Classifiers, Regressors, Random forest
Field	Engineering
Published In	Volume 6, Issue 2, March-April 2024
Published On	2024-04-17
Cite This	Air Quality Prediction using Machine Learning - B.Raviteja, P.Tejaswini, U.Swetha Reddy - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.17192
DOI	https://doi.org/10.36948/ijfmr.2024.v06i02.17192
Short DOI	https://doi.org/gtrfn9

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