Fraudulent transactions pose a significant threat to financial institutions and e-commerce giants like Microsoft. To combat this threat, I have developed a state-of-the-art machine learning model that leverages the power of artificial intelligence to identify and prevent fraudulent activities swiftly and accurately.
active 2023-08-27 → 2023-08-27 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2023-08-27 to 2023-08-27. Pushes: 4 total, peak 4 in a day. Pull requests: 0 total, peak 0 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 |
|---|---|---|---|---|
| collegecoder25 | 4 | 4 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
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.