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Amazon Comprehend
Amazon Comprehend

18
23
+ 1
0
SpaCy
SpaCy

45
26
+ 1
1
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Amazon Comprehend vs SpaCy: What are the differences?

Developers describe Amazon Comprehend as "Discover insights and relationships in text". 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. On the other hand, SpaCy is detailed as "Industrial-Strength Natural Language Processing in Python". 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 and SpaCy can be primarily classified as "NLP / Sentiment Analysis" tools.

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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 are some alternatives to Amazon Comprehend and SpaCy?
          IBM Watson
          It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine.
          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.
          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.
          Wit
          Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.
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