Software Alternatives & Reviews

Gensim VS Amazon Comprehend

Compare Gensim VS Amazon Comprehend and see what are their differences

Gensim logo Gensim

Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora.

Amazon Comprehend logo Amazon Comprehend

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  • Gensim Landing page
    Landing page //
    2023-01-23
  • Amazon Comprehend Landing page
    Landing page //
    2022-02-01

Gensim videos

Word2Vec with Gensim - Python

More videos:

  • Review - Bhargav Srinivasa Desikan - Topic Modelling (and more) with NLP framework Gensim
  • Tutorial - How to Generate Custom Word Vectors in Gensim (Named Entity Recognition for DH 07)

Amazon Comprehend videos

Building Text Analytics Applications on AWS using Amazon Comprehend - AWS Online Tech Talks

More videos:

  • Tutorial - How to Analyse Text with Amazon Comprehend - Sentiment Analysis and Entity Extraction tutorial
  • Review - Analyzing Text with Amazon Elasticsearch Service and Amazon Comprehend - AWS Online Tech Talks

Category Popularity

0-100% (relative to Gensim and Amazon Comprehend)
Natural Language Processing
Spreadsheets
14 14%
86% 86
NLP And Text Analytics
11 11%
89% 89
Data Science And Machine Learning

User comments

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Social recommendations and mentions

Based on our record, Amazon Comprehend should be more popular than Gensim. It has been mentiond 19 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Gensim mentions (9)

  • Understanding How Dynamic node2vec Works on Streaming Data
    This is our optimization problem. Now, we hope that you have an idea of what our goal is. Luckily for us, this is already implemented in a Python module called gensim. Yes, these guys are brilliant in natural language processing and we will make use of it. 🤝. - Source: dev.to / over 1 year ago
  • Is it home bias or is data wrangling for machine learning in python much less intuitive and much more burdensome than in R?
    Standout python NLP libraries include Spacy and Gensim, as well as pre-trained model availability in Hugginface. These libraries have widespread use in and support from industry and it shows. Spacy has best-in-class methods for pre-processing text for further applications. Gensim helps you manage your corpus of documents, and contains a lot of different tools for solving a common industry task, topic modeling. Source: over 1 year ago
  • GET STARTED WITH TOPIC MODELLING USING GENSIM IN NLP
    Here we have to install the gensim library in a jupyter notebook to be able to use it in our project, consider the code below;. - Source: dev.to / almost 2 years ago
  • [Research] Text summarization using Python, that can run on Android devices?
    TextRank will work without any problems. Https://radimrehurek.com/gensim/. Source: about 2 years ago
  • Topic modelling with Gensim and SpaCy on startup news
    For the topic modelling itself, I am going to use Gensim library by Radim Rehurek, which is very developer friendly and easy to use. - Source: dev.to / over 2 years ago
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Amazon Comprehend mentions (19)

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What are some alternatives?

When comparing Gensim and Amazon Comprehend, you can also consider the following products

spaCy - spaCy is a library for advanced natural language processing in Python and Cython.

rasa NLU - A set of high level APIs for building your own language parser

FuzzyWuzzy - FuzzyWuzzy is a Fuzzy String Matching in Python that uses Levenshtein Distance to calculate the differences between sequences.

FastText - Library for efficient text classification and representation learning

Google Cloud Natural Language API - Natural language API using Google machine learning

NLTK - NLTK is a platform for building Python programs to work with human language data.