AQI Prediction Model

AQI Prediction is a data science project that aims to predict the Air Quality Index (AQI) based on various environmental factors such as temperature, humidity, wind speed, and other pollutants. The goal is to create a model that helps in forecasting air quality to better inform the public about pollution levels and health risks.

Features

• AQI Prediction: Predict the Air Quality Index (AQI) based on input features like temperature, humidity, PM2.5, PM10, CO, NO2, Ozone, etc.
• Data Visualization: Visualize trends in the data using graphs and charts.
• Model Performance: Evaluate the model's performance using metrics like accuracy, mean squared error, and R-squared value.
• Real-time Prediction: Input current environmental data and get an instant prediction of the AQI value.

Installation

To run the AQI Prediction system locally, follow these steps to set up the project on your machine.

Prerequisites

Ensure you have the following installed:

• Python 3.x: A Python environment to run the project.
• Git: To clone the repository.

Steps to Install

1. Clone the repository:

   First, clone the repository to your local machine:

   git clone https://github.com/prashantkumar7541/AQI-Prediction-Model.git