In an effort to explore the intersection of deep learning and neural signals, I explored the use of various neural networks in the classification of seizure states. Using the Bonn dataset (https://www.kaggle.com/datasets/quands/eeg-dataset), I transformed the signal into usable segments, extracted features from it, and trained an ANN to 95.25% accuracy, followed by exploring time series architectures including RNNs, LSTMs, GRUs, and more. (In progress)