AQI Prediction using Machine Learning

Problem Overview

This project predicts Air Quality Index (AQI) using environmental pollutant data such as PM2.5, PM10, NO2, and SO2.

Data Source

The dataset was collected from publicly available air quality datasets and processed by computing AQI using CPCB guidelines.

Models Used

• Linear Regression
• Decision Tree Regressor
• Random Forest Regressor (Final Model)

Random Forest was selected due to its superior performance in terms of RMSE and R².

Steps to Run Streamlit App

1. Install dependencies
   pip install streamlit scikit-learn pandas
2. Run the app
   streamlit run app.py