arshia-pelathur/Sentiment-Analysis-and-Text-Classification-with-NLP
View on GitHub ↗Related repositories →This project involves sentiment analysis of textual data using various NLP techniques and machine learning models. It compares the performance of multiple feature extraction methods, including Count Vectorizer, TF-IDF, OneHot Encoding, and Word2Vec, alongside machine learning classifiers such as SVC and Naive Bayes.
active 2024-09-29 → 2025-01-22 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 116 days from 2024-09-29 to 2025-01-22. Pushes: 30 total, peak 25 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: 2 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 |
|---|---|---|---|---|
| arshia-pelathur | 30 | 30 | 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 — 2 stars here means stars gained during the window, not the repo's star count.