Forwarded from Data Science by ODS.ai 🦜
Most common libraries for Natural Language Processing:
CoreNLP from Stanford group:
http://stanfordnlp.github.io/CoreNLP/index.html
NLTK, the most widely-mentioned NLP library for Python:
http://www.nltk.org/
TextBlob, a user-friendly and intuitive NLTK interface:
https://textblob.readthedocs.io/en/dev/index.html
Gensim, a library for document similarity analysis:
https://radimrehurek.com/gensim/
SpaCy, an industrial-strength NLP library built for performance:
https://spacy.io/docs/
Source: https://itsvit.com/blog/5-heroic-tools-natural-language-processing/
#nlp #digest #libs
CoreNLP from Stanford group:
http://stanfordnlp.github.io/CoreNLP/index.html
NLTK, the most widely-mentioned NLP library for Python:
http://www.nltk.org/
TextBlob, a user-friendly and intuitive NLTK interface:
https://textblob.readthedocs.io/en/dev/index.html
Gensim, a library for document similarity analysis:
https://radimrehurek.com/gensim/
SpaCy, an industrial-strength NLP library built for performance:
https://spacy.io/docs/
Source: https://itsvit.com/blog/5-heroic-tools-natural-language-processing/
#nlp #digest #libs
CoreNLP
High-performance human language analysis tools, now with native deep learning modules in Python, available in many human languages.