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rasa NLU
rasa NLU

22
28
+ 1
7
Swift AI
Swift AI

4
17
+ 1
0
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rasa NLU vs Swift AI: What are the differences?

Developers describe rasa NLU as "Open source, drop-in replacement for NLP tools like wit.ai". 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. On the other hand, Swift AI is detailed as "A.I. and machine learning library written in Swift". Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!.

rasa NLU and Swift AI are primarily classified as "NLP / Sentiment Analysis" and "Machine Learning" tools respectively.

rasa NLU and Swift AI are both open source tools. rasa NLU with 5.77K GitHub stars and 1.7K forks on GitHub appears to be more popular than Swift AI with 5.58K GitHub stars and 542 GitHub forks.

What is rasa NLU?

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.

What is Swift AI?

Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!
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          What are some alternatives to rasa NLU and Swift AI?
          Dialogflow
          Give users new ways to interact with your product by building engaging voice and text-based conversational apps.
          SpaCy
          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.
          Google Cloud Natural Language API
          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.
          Gensim
          It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
          Amazon Comprehend
          Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.
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