Project information
- Problem: Fraud Detection
- ML Areas: Anomaly Detection
- Learning technique: Supervised Learning - Semi-Supervised Learning
- Tools: Python, Pytorch, Jupyter Notebook
- Project date: May 2020
- Project URL: Fraud Detection project
Description
Goal: Detect frauds, given transitions data from kaggle dataset
Technical Solutions:
- Autoencoder - Semi-supervised Learning
- Random Forest - Supervised Learning
Evaluation: AUC
Results: