Description: Create a spam email classifier using Natural Language Processing (NLP) techniques. Train models like Naive Bayes on spam datasets. Libraries: nltk, scikit-learn, pandas Skills: Text classification, feature extraction (TF-IDF, Bag of Words)
active 2024-09-25 → 2024-09-27 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 3 days from 2024-09-25 to 2024-09-27. Pushes: 7 total, peak 5 in a day. Pull requests: 2 total, peak 1 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 |
|---|---|---|---|---|
| Hamza-Rafique | 9 | 7 | 2 | 0 |
Recent activity
Latest issues, pull requests and releases
- Pull request#1Hamza-Rafique2024-09-27 19:51
- Pull request#1Hamza-Rafique2024-09-26 09:50
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.