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UBIAI vs SpaCy: What are the differences?
Developers describe UBIAI as "An easy-to-use text annotation tool for NLP applications". It is an efficient and easy-to-use text annotation tool for Natural Language Processing (NLP) applications. With this, you can train an NLP model in few hours by collaborating with team members and using the machine learning auto-annotation feature. 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.
UBIAI can be classified as a tool in the "Data Labeling as a Service" category, while SpaCy is grouped under "NLP / Sentiment Analysis".
SpaCy is an open source tool with 17.2K GitHub stars and 3.09K GitHub forks. Here's a link to SpaCy's open source repository on GitHub.
Pros of SpaCy
- Speed12
- No vendor lock-in2
Pros of UBIAI
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Cons of SpaCy
- Requires creating a training set and managing training1
