The online payment fraud analysis project follows several step approach from data preprocessing through model evaluation, result comparison and final model selection, using transaction patterns to identify fraud indicators including account draining, suspicious transfers, and balance inconsistencies.

Stroke prediction using machine learning (LogReg, RF, GBoost, LightGBM) with class imbalance handling and threshold optimisation