This repository contains a regression-based model to predict the monthly average air quality in Madrid using historical data. The data includes daily air quality measurements and metadata related to the measurement stations.

Run the Jupyter Notebook air_quality_prediction.ipynb to train and evaluate the regression model

##Dataset Overview The dataset includes:

Metadata about the location and measurement point: PROVINCIA, MUNICIPIO, ESTACION, MAGNITUD, and PUNTO_MUESTREO. Year and month of the measurement: ANO and MES. Daily measurements of air quality from D01 to D31. Verification or validation flags for the corresponding daily measurements from V01 to V31.

The model used is a Linear Regression model from the scikit-learn library. The target variable is the monthly average air quality derived from the daily measurements.

The model achieved an RMSE of approximately 55.66 on the test set, indicating the average error of the model's predictions.