This project has applied Machine Learning and Deep Learning techniques to analyse and predict the Air Quality in Beijing.

Machine Learning model which uses closed-form solution of Locally Weighted Regression (LOWESS) Algorithm to predict the Quality of Air

PurpleAirSF: datasets for realistic air quality forecasting

This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.

This project aims at forecasting the PM2.5 concentration using the other environmental factors.

REST API for real-time air quality index (AQI) and pollutant data. Query by city name or GPS coordinates.

Predicting PM10 air particles using recurrent neural networks (RNN, GRU, LSTM)

Automated MLOps for Urban Air Quality is a serverless AI system forecasting PM2.5 levels for Karachi, Pakistan. It automates the entire machine learning lifecycle from hourly data ingestion to daily model retraining, predicting air quality for 24, 48, and 72 hour horizons.

Exploring Machine Learning Models to forecast daily PM2.5 concentration using meteorological parameters in Hetauda, Nepal.

Air Quality Prediction for Smart Cities Using Multi-Layer Perceptron

Indoor Air Quality Predictions and Monitoring