🧪 Classical ML Drug Discovery

Build defensible molecular machine-learning workflows with Random Forest (RF), Support Vector Machine/Regression (SVM/SVR), and Gradient Boosting (GB)—then turn predictions into a diverse, uncertainty-aware experimental shortlist rather than unsupported claims.

This skill is for computational decision support. It never treats a model score as proof of binding, efficacy, safety, mechanism, or clinical utility.