Google Cloud Natural Language API vs rasa NLU

Google Cloud Natural Language API

29
75
+ 1
0
rasa NLU

57
123
+ 1
18
Add tool

Google Cloud Natural Language API vs rasa NLU: What are the differences?

Developers describe Google Cloud Natural Language API as "Derive insights from unstructured text using Google machine learning". 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. On the other hand, rasa NLU is detailed 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.

Google Cloud Natural Language API and rasa NLU belong to "NLP / Sentiment Analysis" category of the tech stack.

rasa NLU is an open source tool with 5.76K GitHub stars and 1.7K GitHub forks. Here's a link to rasa NLU's open source repository on GitHub.

Pros of Google Cloud Natural Language API
Pros of rasa NLU
    No pros available

    Sign up to add or upvote prosMake informed product decisions

    Cons of Google Cloud Natural Language API
    Cons of rasa NLU

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    What is 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.

    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 companies use Google Cloud Natural Language API?
    What companies use rasa NLU?

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with Google Cloud Natural Language API?
    What tools integrate with rasa NLU?
    What are some alternatives to Google Cloud Natural Language API and rasa NLU?
    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.
    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.
    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.
    FastText
    It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.
    AlchemyAPI
    AlchemyLanguageTM is the world’s most popular natural language processing service. AlchemyVisionTM is the world’s first computer vision service for understanding complex scenes. AlchemyAPI is used by more than 40,000 developers across 36 countries and a wide variety of industries to process over 3 billion texts and images every month.
    See all alternatives
    Interest over time