Flair

7
39
+ 1
1
Hogan.js

304
38
+ 1
3
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Flair vs Hogan.js: What are the differences?

Flair: A simple framework for natural language processing. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification; Hogan.js: A compiler for the Mustache templating language. Hogan.js is a 3.4k JS templating engine developed at Twitter. Use it as a part of your asset packager to compile templates ahead of time or include it in your browser to handle dynamic templates.

Flair can be classified as a tool in the "NLP / Sentiment Analysis" category, while Hogan.js is grouped under "Templating Languages & Extensions".

Flair and Hogan.js are both open source tools. It seems that Flair with 6.53K GitHub stars and 666 forks on GitHub has more adoption than Hogan.js with 5K GitHub stars and 438 GitHub forks.

Pros of Flair
Pros of Hogan.js

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What is Flair?

Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.

What is Hogan.js?

Hogan.js is a 3.4k JS templating engine developed at Twitter. Use it as a part of your asset packager to compile templates ahead of time or include it in your browser to handle dynamic templates.
What companies use Flair?
What companies use Hogan.js?
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    What tools integrate with Flair?
    What tools integrate with Hogan.js?
    What are some alternatives to Flair and Hogan.js?
    Keen
    Keen is a powerful set of API's that allow you to stream, store, query, and visualize event-based data. Customer-facing metrics bring SaaS products to the next level with acquiring, engaging, and retaining customers.
    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.
    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.
    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.
    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.
    See all alternatives
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