fingeredman/advanced-text-mining
TEANAPS 라이브러리를 활용한 자연어 처리와 텍스트 분석 방법론에 대해 다룹니다.
This project offers comprehensive learning materials and practical exercises for analyzing text data. It takes raw, unstructured text (like reviews, news, or social media posts) and transforms it into actionable insights such as sentiment analysis, topic trends, or categorized documents. Researchers, data analysts, and students looking to apply advanced text mining techniques to Korean text will find this valuable.
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Use this if you need to understand and apply various text mining techniques to real-world Korean text data, from basic preprocessing to advanced machine learning and deep learning models.
Not ideal if you are looking for a plug-and-play software solution rather than educational content and practical code examples for learning text mining.
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17
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Jupyter Notebook
License
Apache-2.0
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Last pushed
Sep 18, 2022
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