This project aims to build a machine learning model that can classify tweets as disaster-related or not, based on their text content. The project utilizes Natural Language Processing (NLP) techniques to preprocess and analyze the text and trains several machine learning models to predict the classification of each tweet.
active 2023-10-14 → 2024-05-19 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 219 days from 2023-10-14 to 2024-05-19. Pushes: 13 total, peak 7 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 |
|---|---|---|---|---|
| elsayedelmandoh | 13 | 13 | 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.