textClassifier and a-PyTorch-Tutorial-to-Text-Classification
These are ecosystem siblings—both are independent educational implementations of the same hierarchical attention network architecture for document classification, with the first being a ready-to-use classifier and the second being a tutorial-oriented codebase for learning the approach.
About textClassifier
richliao/textClassifier
Text classifier for Hierarchical Attention Networks for Document Classification
This tool helps you automatically sort documents or pieces of text into categories. You provide a collection of text data, and it identifies the core topics or sentiments within each piece, assigning it to a specific label. It's designed for data analysts or researchers who need to categorize large volumes of textual information efficiently.
About a-PyTorch-Tutorial-to-Text-Classification
sgrvinod/a-PyTorch-Tutorial-to-Text-Classification
Hierarchical Attention Networks | a PyTorch Tutorial to Text Classification
This is a tutorial for deep learning developers who want to build a model that can automatically label text documents with specific categories. You provide the text content, and the model classifies it into predefined categories, also highlighting the most important words and sentences that led to its decision. This is ideal for machine learning engineers and researchers working with natural language processing.
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