SleepStageClassifier is a machine learning project aimed at classifying sleep stages from polysomnographic (PSG) recordings contained in the sleep-edf database. This project explores various machine learning models, from traditional algorithms to advanced deep learning techniques, to accurately classify sleep stages based on EEG, EOG, and EMG signals.
data/: Directory to store the sleep-edf dataset files. πnotebooks/: Jupyter notebooks for exploratory data analysis and model experimentation. πsrc/: Source code for the project, including data preprocessing, model training, and evaluation scripts. π»models/: Trained model files. π€requirements.txt: A list of python package dependencies. π