atchudhansg/Parallelized-Spam-Filter-Using-Logistic-Regression-and-TF-IDF-Vectorization
View on GitHub ↗Related repositories →This project aims to develop a robust email spam filter using machine learning techniques, like logistic regression for classification model and TF-IDF vectorization for feature extraction from email text. By deploying parallelization techniques, the project optimizes the feature extraction process, enhancing the efficiency of the spam filter.
active 2024-04-11 → 2024-04-11 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-04-11 to 2024-04-11. 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 |
|---|---|---|---|---|
| atchudhansg | 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.