This repo contains the code and analysis for predicting student performance in a Datathon competition. Key features include family income, teacher quality, and distance from home. Machine learning models like Logistic Regression and Random Forest are used to classify students as "pass" or "fail" and identify factors affecting academic success.
active 2024-10-09 → 2024-10-14 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 6 days from 2024-10-09 to 2024-10-14. Pushes: 10 total, peak 10 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 |
|---|---|---|---|---|
| TimmyTobby | 8 | 8 | 0 | 0 |
| Victory0007 | 2 | 2 | 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.