Amir-Ali/Air_Quality_Index_Prediction_Model

🌫️ Air Quality Prediction Dashboard

This is a complete machine learning project that predicts the Air Quality Index (AQI) using a trained Random Forest Regressor. The app is built using Streamlit and includes interactive EDA dashboards and a real-time prediction tool.

📌 Project Highlights

✅ Predicts AQI (Air Quality Index) based on air pollutant concentrations ✅ Built-in Exploratory Data Analysis (EDA) with Seaborn and Matplotlib ✅ Clean and responsive Streamlit UI ✅ Final model: Random Forest Regressor ✅ Fully interactive interface with real-time prediction ✅ Suitable for academic, portfolio, or real-world use

📂 Dataset

• —Source: Air Quality Index
• —Target Column: AQI
• —Features Used:
• —CO
• —CO₂
• —NO₂
• —SO₂
• —O₃
• —PM2.5
• —PM10

📊 App Features

🧠 Tools & Models Used

• —✅ Random Forest Regressor
• —✅ Pandas, Scikit-learn
• —✅ Seaborn, Matplotlib
• —✅ Streamlit for building the web UI
• —✅ Joblib for saving the compressed model and also loading the model

▶ How to Run Locally

# Step 1: Install dependencies
pip install -r requirements.txt

# Step 2: Run the Streamlit app
streamlit run app.py