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https://github.com/msthamizh/toxicity-detection-in-tweets
Developed a machine learning model to classify tweets as toxic or non-toxic using NLP techniques like tokenization, lemmatization, and TF-IDF vectorization. Evaluated multiple classifiers and analyzed performance using classification reports, confusion matrices, and ROC-AUC curves.
https://github.com/msthamizh/toxicity-detection-in-tweets
machine-learning natural-language-processing nltk python
Last synced: about 1 month ago
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Developed a machine learning model to classify tweets as toxic or non-toxic using NLP techniques like tokenization, lemmatization, and TF-IDF vectorization. Evaluated multiple classifiers and analyzed performance using classification reports, confusion matrices, and ROC-AUC curves.
- Host: GitHub
- URL: https://github.com/msthamizh/toxicity-detection-in-tweets
- Owner: MSThamizh
- Created: 2024-11-21T15:01:09.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2024-11-21T15:44:11.000Z (about 2 months ago)
- Last Synced: 2024-11-21T16:23:40.004Z (about 2 months ago)
- Topics: machine-learning, natural-language-processing, nltk, python
- Language: Jupyter Notebook
- Homepage:
- Size: 3.04 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0