fix: accept HEAD requests on /health so UptimeRobot monitoring works

Step 8: add 28 automated tests covering preprocessing, models, and API

Step 7: FastAPI with /predict /health endpoints, V1-V28 inference explanation in README

Step 6: select xgboost_tuned as final model with full comparison and reasoning in README

Step 6: switch to CatBoost as final model, add tune_catboost.py, rename xgboost_final to xgboost_tuned

Step 6: model comparison charts, XGBoost GridSearchCV tuning, real benchmark scores in README

Step 5: remove SVM/KNN/MLP, clarify 10 pkl files in models dir (9 models + scaler)

Step 4: MLflow setup with SQLite backend and experiment tracking helpers

Step 3: data preprocessing pipeline with scaling, train/test split, and SMOTE

Step 1: project setup, folder structure, and environment