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Gensim vs SpaCy: What are the differences?
What is Gensim? A python library for Topic Modelling. 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.
What is SpaCy? 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.
Gensim and SpaCy belong to "NLP / Sentiment Analysis" category of the tech stack.
Gensim is an open source tool with 9.65K GitHub stars and 3.52K GitHub forks. Here's a link to Gensim's open source repository on GitHub.
According to the StackShare community, SpaCy has a broader approval, being mentioned in 14 company stacks & 11 developers stacks; compared to Gensim, which is listed in 3 company stacks and 5 developer stacks.
Pros of Gensim
Pros of SpaCy
- No vendor lock-in2
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Cons of Gensim
Cons of SpaCy
- Requires creating a training set and managing training1