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Status:
- Pick a feasible dataset and method to start with: kannada dataset, tagging sentiment for movie reviews.
- Studied several papers
- Worked on an horseheard implementation.
- Picked a feasible dataset and method to start with: kannada dataset, tagging sentiment for movie reviews.
- Worked on a paper.
- Studied several papers,
- started to work on a streamlit demo
Open tasks:
- Focus on making a baseline experiment for sentiment classification using classical methods, such as Transformers. PLEASE DO NO AVOID !!!!
- Prepare a survey paper for school journal or a conference. Use and correct the draft form the beginning. PLEASE DO NO AVOID !!!!
- Try to prepare an experiment with the selected dataset. https://git.kemt.fei.tuke.sk/mg240ia/Hate_Speech_IMAYFLY_and_HORSEHERD
- Focus on making a baseline experiment for sentiment classification using classical methods, such as Transformers.
- For preparing a web application with demo, learn about streamlit. In progress: https://git.kemt.fei.tuke.sk/mg240ia/Hate-Speech-Detector-Streamlit
Read Papers :