Geomagnetic Storm Prediction using Machine Learning

In this project, I developed a machine learning model to predict geomagnetic storms (Kp index), which directly impact satellite and communication systems.

I applied time series forecasting techniques using multiple models, including Random Forest, LightGBM, and LSTM.

The workflow included data cleaning, exploratory data analysis, feature engineering, and model training with hyperparameter tuning to improve performance.

The results showed strong predictive capability, making the model useful as an early warning system for space weather risks.

Tools & Technologies:

- Python

- Scikit-learn

- TensorFlow / Keras

- Pandas

This project demonstrates my ability to apply AI techniques to real-world aerospace problems.