This project classifies grayscale images of handwritten alphabets (A-Z) using machine learning and deep learning techniques. Experiments include SVMs, custom logistic regression, and neural networks with performance evaluated through confusion matrices and F1-scores. The best model is saved and tested with custom input.
active 2025-01-09 → 2025-01-09 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-01-09 to 2025-01-09. 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 |
|---|---|---|---|---|
| salmahazem14 | 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.