kushalchauhan98/bcn-cnn-text-classification
Text classification experiments using TextCNNs and Bi-attentive Classification Networks
This project helps categorize text documents by analyzing their content to assign a relevant label or class. It takes raw text data as input and produces categorized text outputs, which can be useful for organizing large datasets or automating content analysis. Researchers and data analysts working with textual information would find this tool beneficial for classification tasks.
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Use this if you need to automatically assign categories or labels to text documents based on their content, like sorting customer feedback or identifying document types.
Not ideal if you require real-time, highly scalable text classification on massive data streams or if you need to understand the nuances of text sentiment rather than just its category.
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Last pushed
Feb 18, 2019
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