EdGENetworks/attention-networks-for-classification

Hierarchical Attention Networks for Document Classification in PyTorch

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This helps categorize written documents like customer reviews, articles, or legal texts by understanding their natural structure—words forming sentences, and sentences forming full documents. It takes raw text documents as input and outputs a classification or category for each document. A data scientist or machine learning engineer focused on natural language processing would use this to build more accurate text classification systems.

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Use this if you are developing a text classification system and want to leverage the hierarchical structure of documents to improve model performance.

Not ideal if you need a pre-trained, production-ready model for immediate use or are not comfortable working with PyTorch implementations.

document-classification natural-language-processing text-analytics machine-learning-engineering

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