Upload README.md

README.md

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----
-title: AirQualityPredictorApp
-emoji: 🌍
-colorFrom: green
-colorTo: blue
-sdk: gradio
-sdk_version: 5.36.2
-app_file: app.py
-pinned: false
-license: mit
-short_description: A Gradio app for predicting AQI and classifying air quality.
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Air Quality Prediction and Classification
+
+This Gradio app predicts the Air Quality Index (AQI) and classifies air quality as "Safe" or "Unsafe" based on pollutant levels (PM2.5, PM10, NO2, CO) and weather conditions (temperature, humidity). It addresses urban air pollution, a critical public health issue.
+
+## How to Use
+1. Use sliders to input pollutant levels and weather conditions.
+2. View predicted AQI from Linear Regression, Polynomial Regression, Ridge Regression, and Random Forest.
+3. See classifications from Logistic Regression and Random Forest.
+4. Check the bar plot comparing model predictions.
+
+## Model Details
+- **Dataset**: Synthetic air quality data (inspired by UCI Air Quality Dataset).
+- **Features**: PM2.5, PM10, NO2, CO, Temperature, Humidity, K-means cluster labels.
+- **Models**: Linear Regression, Polynomial Regression, Ridge Regression, Random Forest (regression and classification), Logistic Regression.
+- **Concepts**: Unsupervised learning, feature engineering, regularization, ensemble learning, bias-variance tradeoff.
+
+## Real-World Impact
+This app can inform air quality monitoring and health advisories in urban areas.