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README.md
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sdk: static
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### Yapılan proje adımları aşağıda yer almaktadır.
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![plot](/img/akış.drawio.png)
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The steps to create this dataset are as follows.
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- Step 1: Data Scraping Tool: https://github.com/Teknofest-Nane-Limon/twitter-scraper
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- Step 2: Data Labeling Tool: https://github.com/Teknofest-Nane-Limon/easy-data-labeling-engine
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- Productization of labeled data: https://huggingface.co/datasets/nanelimon/turkish-social-media-bullying-dataset
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- Step 3: Data Cleaning Tool: https://github.com/Teknofest-Nane-Limon/text-data-cleaner
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- Step 4: Data Modeling:
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- 4.1. Analysis and trials notebook for TFID: https://github.com/Teknofest-Nane-Limon/tfidf-model-turkish-bullying
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- 4.2 Analysis and essays notebook for Bert Mobel: https://github.com/Teknofest-Nane-Limon/bert-base-turkish-bullying/blob/main/bert-cv.ipynb%20-%20Colaboratory.pdf & bert-cv.ipynb
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- 4.3 Modeling notebook with hyper parameters from Bert Model: https://github.com/Teknofest-Nane-Limon/bert-base-turkish-bullying/blob/main/bert-base-turkish-bullying-best-parameter.ipynb
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- Step 5: Productization of the Model:
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- 5.1 Python FastAPI: https://github.com/Teknofest-Nane-Limon/turkish-bullying-api
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- 5.2 Hugging Face : https://huggingface.co/nanelimon/bert-base-turkish-bullying
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## For Example
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> Cinsiyetçilik Örneği:
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![plot](/img/Cinsiyetçilik.jpeg)
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> Irkçılık Örneği:
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![plot](/img/Irkçılık.jpeg)
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> Kızdırma Örneği:
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![plot](/img/Kızdırma.jpeg)
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> Nötr Örneği
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![plot](/img/Nötr.jpeg)
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sdk: static
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pinned: false
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