This project utilizes difference deep-learning algorithms to detect fraud operations on banking systems ( classification problem )
the objective was to build ANN models from scratch using keras sequential-models , trying different combination of layers and parameters to improve efficiency , accuracy and reduce overfitting then compare this models with with a pre-trained classification model by (TabNet)
You can view the presentation slides here.