yala/text_nn
Text classification models. Used a submodule for other projects.
This project helps data scientists and machine learning engineers build text classification models. It takes raw text data (like news articles or product reviews) and GloVe word embeddings as input, then outputs classifications for each text along with 'rationales' – the specific text snippets that led to that classification. This helps practitioners understand and explain why a model made a particular decision.
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Use this if you need to classify text documents and also want to understand which parts of the text are most influential in the classification decision.
Not ideal if you are looking for a plug-and-play solution without any coding, or if you do not have access to pre-trained GloVe word embeddings.
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Jupyter Notebook
License
MIT
Last pushed
May 28, 2019
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