bkj/ulm-basenet
Implementation of ULMFit algorithm for text classification via transfer learning
This tool helps data scientists and machine learning engineers classify text documents more effectively, especially when they have limited labeled data. It takes raw text data as input and outputs a highly accurate text classification model, suitable for tasks like sentiment analysis or topic labeling. It's designed for practitioners who want to leverage advanced transfer learning techniques for natural language processing.
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Use this if you need to build a robust text classification model with minimal labeled training data, by applying transfer learning techniques.
Not ideal if you are looking for a plug-and-play solution without any coding or machine learning expertise.
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95
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18
Language
Python
License
—
Last pushed
Feb 12, 2019
Commits (30d)
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