The goal of this project is to create word embeddings using the Word2Vec model with Gensim and use these embeddings in machine learning tasks such as text classification, clustering, or sentiment analysis. The project demonstrates how to build word embeddings from a corpus and how to use these embeddings as input to a machine learning model.
active 2024-09-11 → 2024-09-11 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-09-11 to 2024-09-11. 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 |
|---|---|---|---|---|
| 1216-dev | 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.