Classification project using Self-Organizing Maps (SOM) to differentiate patients and healthy subjects from marker data, encompassing network construction, training, and testing phases.

Implement simple ML models for activity recognition using accelerometer data. Includes feature extraction, vector classification, Grid Search CV, and Decision Tree models. Built with Python and Anaconda.