AlchemyAPI vs Amazon Comprehend vs SpaCy

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AlchemyAPI

19
35
+ 1
0
Amazon Comprehend

50
138
+ 1
0
SpaCy

217
291
+ 1
14
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Pros of AlchemyAPI
Pros of Amazon Comprehend
Pros of SpaCy
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      • 12
        Speed
      • 2
        No vendor lock-in

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      Cons of AlchemyAPI
      Cons of Amazon Comprehend
      Cons of SpaCy
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        • 2
          Multi-lingual
        • 1
          Requires creating a training set and managing training

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        - No public GitHub repository available -
        - No public GitHub repository available -

        What is 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.

        What is 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.

        What is 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.

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        What companies use AlchemyAPI?
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        What tools integrate with AlchemyAPI?
        What tools integrate with Amazon Comprehend?
        What tools integrate with SpaCy?
        What are some alternatives to AlchemyAPI, Amazon Comprehend, and SpaCy?
        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.
        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.
        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.
        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.
        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.
        See all alternatives