mpuig/textclassification
A brief overview of how to use fastText to train powerful text classifiers in a python notebook.
This project helps you automatically sort text documents like emails, social media posts, or customer feedback into predefined categories or tags. You provide a collection of text examples, each already labeled with its correct category, and it learns to classify new, unlabeled texts. This is ideal for anyone who needs to categorize large volumes of text data efficiently, such as content managers, customer support teams, or researchers.
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Use this if you have a dataset of text documents that are already manually categorized and you want to build a system to automatically assign categories to new, similar documents.
Not ideal if you don't have existing labeled text data to train on, or if you need to extract specific entities or sentiments rather than just broad categories.
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Jun 18, 2017
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