Segment from main codebase detailing the methods for neural network enhanced sleep state classification. This project has been deployed for internal usage.

A Jupyter Notebook is available for some basic visualizations of the dataset. Majority of the pre-processing is performed via MATLAB.

This project was built on Python 3.6. An Anaconda environment in ./configs/environment.yml is prepared for installation for new users.

main.py can be used to explore the model creation. The SleepClassifier class can be constructed, and then call the methods fit() or predict()