Air Quality Clustering Analysis

A machine learning project that applies K-Means clustering to analyze air quality sensor data, using dimensionality reduction and visualization techniques to identify patterns in environmental measurements.

📁 Dataset

The project uses the Air Quality UCI dataset, which contains:

• 9,358 hourly averaged responses from chemical sensors
• 8 sensor features: CO, NMHC, NOx, NO2, O3, Temperature, Relative Humidity, Absolute Humidity
• Data collected from March 2004 to February 2005

🛠️ Setup

1. Clone the repository:

git clone https://github.com/Gianluca-Coppola/Clustering.git
cd Clustering

2. Install required packages:

pip install -r requirements.txt