Regularized Neural Network for Regional Air-Quality Forecasting
▼Built a compact, regularized TensorFlow neural network to forecast NO2, CO, SO2, 03, PM2-5, PM10 particles over Greece and deliver predictions to an interactive 3D globe. Data was taken from NASA's GIOVANNI interface. Trained on a standardized (z-scored) target, and used gradient clipping to keep learning stable. Generalization was enforced with out-of-year validation (train on earlier years, test on the last year), while ReduceLROnPlateau and EarlyStopping (best-weights restore) prevented overfitting and landed training at the strongest epoch. Project was developed over 2 days for NASA's Space Apps Challenge Hackathon in Thessaloniki where i worked together with 5 other people and integrated the neural network on an interactive webpage.