This is a TA meterial for Machine Learning basics and must-know opertion. Overall implementation is without Machine Learning open source library, instead, it's all by basic scientific library (like Numpy, Pandas, Matplotlib, Seaborn...). So, it will help you have a better understand of how you can master the underlying architecture of ML algorithm
active 2025-03-05 → 2025-03-05 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-03-05 to 2025-03-05. Pushes: 3 total, peak 3 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: 1 total, peak 1 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 |
|---|---|---|---|---|
| SuleynanAuir | 3 | 3 | 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 — 1 stars here means stars gained during the window, not the repo's star count.