tweet-disaster-detection and Kaggle-Disaster-Tweets-DeBERTa

tweet-disaster-detection
32
Emerging
Kaggle-Disaster-Tweets-DeBERTa
21
Experimental
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 12/25
Maintenance 10/25
Adoption 0/25
Maturity 11/25
Community 0/25
Stars: 5
Forks: 1
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: —
Forks: —
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
No Package No Dependents

About tweet-disaster-detection

deepmancer/tweet-disaster-detection

fine-tuned BERT and scikit-learn models for real-time classification of disaster-related tweets, using TensorFlow, Keras, and Transformers. .

This project helps emergency responders and crisis management teams quickly identify genuine disaster-related tweets amidst the vast amount of social media noise. It takes incoming tweets and classifies them in real-time as either indicating a disaster or not, providing critical, timely information. Anyone involved in public safety, emergency services, or humanitarian aid who monitors social media for incident awareness would benefit.

emergency-response crisis-management public-safety social-media-monitoring disaster-preparedness

About Kaggle-Disaster-Tweets-DeBERTa

YukiFujimatsu/Kaggle-Disaster-Tweets-DeBERTa

SOTA-level NLP classification model for predicting real disaster tweets using microsoft/deberta-v3-large.

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