Google Cloud Natural Language API vs MonkeyLearn vs rasa NLU

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Google Cloud Natural Language API

46
131
+ 1
0
MonkeyLearn

15
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+ 1
1
rasa NLU

121
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+ 1
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Pros of Google Cloud Natural Language API
Pros of MonkeyLearn
Pros of rasa NLU
    Be the first to leave a pro
    • 1
      Easy to use
    • 9
      Open Source
    • 6
      Docker Image
    • 6
      Self Hosted
    • 3
      Comes with rasa_core
    • 1
      Enterprise Ready

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    Cons of Google Cloud Natural Language API
    Cons of MonkeyLearn
    Cons of rasa NLU
    • 2
      Multi-lingual
      Be the first to leave a con
      • 4
        No interface provided
      • 4
        Wdfsdf

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      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 MonkeyLearn?

      Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.

      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.

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      Jobs that mention Google Cloud Natural Language API, MonkeyLearn, and rasa NLU as a desired skillset
      What companies use Google Cloud Natural Language API?
      What companies use MonkeyLearn?
      What companies use rasa NLU?

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      What tools integrate with Google Cloud Natural Language API?
      What tools integrate with MonkeyLearn?
      What tools integrate with rasa NLU?

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      What are some alternatives to Google Cloud Natural Language API, MonkeyLearn, and rasa NLU?
      Transformers
      It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
      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.
      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.
      Sentence Transformers
      It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.
      See all alternatives