You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage. | It is an open-source no-code system for text annotation and building text classifiers. With this, domain experts can quickly create custom Natural Language Processing (NLP) models by themselves, with no dependency on NLP experts. No AI knowledge needed; from task definition to working model in just a few hours! |
| - | Extensible architecture;
Open source;
No AI knowledge needed;
From task definition to working model in just a few hours |
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GitHub Stars - | GitHub Stars 269 |
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rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.

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