DataScience_Project2

Application of Machine Learning to Epileptic Seizure Detection.

This project is to follow Knowledge Discovery and Data Mining steps to detect and classify the onset of Epileptic seizures in patient-specific EEG data. Performed signal processing of the raw EEG data and designed three classification models to recognize/predict seizure during the first 24 hours of EEG recordings. Implementation is done in Jupiter Notebook to perform preliminary analysis & visualize data using Matplotlib. Used sensitivity/ specificity analysis and 5-fold cross-validation, along with MCC for Validation.