persiyanov/skip-thought-tf
An implementation of skip-thought vectors in Tensorflow
This project helps developers convert sentences into numerical vectors that capture their meaning, even if the sentences are phrased differently. You feed it a collection of text documents, and it outputs a numerical representation (vector) for each sentence. This is useful for engineers building applications that need to understand text, such as recommendation systems, search engines, or content categorization tools.
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Use this if you are a machine learning engineer or data scientist looking to generate meaningful, fixed-length numerical representations of sentences from your text data.
Not ideal if you are looking for a ready-to-use application for text analysis and don't want to work with code or integrate a model into a larger system.
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Language
Python
License
MIT
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Last pushed
Mar 24, 2023
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