Code for training G1 humanoid with a foothold prediction model
A machine learning web app that predicts whether a patient is at risk of heart disease, based on 13 clinical features. Built with scikit-learn (Random Forest) and deployed with Streamlit.
Train in Google Colab → deploy a live "Claim Compass" app on Streamlit Community Cloud. This predicts a continuous claim amount (regression), not a yes/no classification.