Fraud Detection for E-Commerce and Banking Transactions. This project builds machine learning models to analyze transaction data, integrating geolocation and pattern recognition to detect fraud. It enables real-time monitoring and prevention for improved security.
active 2024-10-18 → 2024-10-31 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 14 days from 2024-10-18 to 2024-10-31. Pushes: 59 total, peak 21 in a day. Pull requests: 8 total, peak 3 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| WildCayote | 67 | 59 | 8 | 0 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.