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AQI-prediction using Nested LSTM and wavelet transform (WT) based on Keras.

This repository hosts the source code and dataset for predicting air quality using AQI values. It includes an initial Exploratory Data Analysis (EDA) followed by a comparative analysis of four machine learning models: KNN, Naive Bayes Classifier, Random Forest Classifier, and Extreme ML.

Aqi Prediction Project

This project analyzes the Indian Climate Dataset (2024–2025) to understand environmental factors influencing Air Quality Index (AQI). It combines exploratory data analysis (EDA), predictive modeling (regression & classification), and unsupervised clustering to provide insights into climate patterns and pollution levels.

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Second place solution in the H2O World India Hackathon held in April 2023.

A time series model for AQI prediction using Random Forest, LSTM and PSO

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AI-powered air quality prediction system using satellite data and machine learning

AQI prediction using Machine Learning (Linear Regression, Random Forest, XGBoost) with XGBoost as the best model, featuring data preprocessing, training, evaluation, and tuning for accurate air pollution insights. 🚀

Air Quality Index Predictor

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Predicted Air Quality Index (AQI) using KNN and Decision Tree models on historical air quality data. Explored pollutants, handled nulls, and visualized results. Enhance environmental insights with this Python-based project.

Developed a machine learning model to predict Air Quality Index (AQI) for Mumbai using historical air quality data. The project focuses on handling missing values, preprocessing data, and evaluating the performance of multiple regression models. Decision Tree and Random Forest models demonstrated superior performance.

The study analyses the AQI and predicts before and after lockdown of COVID-19 in India.

Building a real time Air Quality monitoring system that will detect (using IOT Device), monitor & analyse the current and past data using ML to derive the useful insights.

This is a website that uses our custom model that we have developed for our thesis. It predicts Air Quality Indexing (AQI) for an uploaded image in real-time. It also shows lime explanation that shows the regions of image that is important to the model (mostly sky areas).

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a predictive model to estimate Air Quality Index (AQI) using environmental datasets.

Air Quality Prediction App

This project focuses on time series forecasting of Air Quality Index (AQI) using classical statistical models like ARIMA and deep learning-based LSTM models.

A R project to predict the Air Quality Index in India

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Time-series based Air Quality Index (AQI) prediction model built using multi-city Indian pollution data. Includes EDA, feature engineering (log & lag features), and Random Forest/XGBoost models achieving 0.90+ R² accuracy.

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