This project demonstrates Logistic Regression, Random Forest, Gradient Boosting, Decision Tree, and Neural Network models. It includes data preprocessing, model evaluation, confusion matrices, and feature importance visualization. Skills data encoding/scaling is covered. Models achieved up to 100% accuracy; Neural Network reached 95.69% accuracy.
active 2024-07-20 → 2024-07-20 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-07-20 to 2024-07-20. Pushes: 1 total, peak 1 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 |
|---|---|---|---|---|
| TarekkMU1911 | 1 | 1 | 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.