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NLTK: https://github.com/nltk/nltk https://github.com/nltk/nltk with the documentation at http://www.nltk.org http://www.nltk.org. I found the code easy to foll
by deepaksurti 11y ago
NLTK: https://github.com/nltk/nltk https://github.com/nltk/nltk with the documentation at http://www.nltk.org http://www.nltk.org. I found the code easy to follow through.
I referred to it when adding tests for tokenizers in a common lisp NLP application: https://github.com/vseloved/cl-nlp/ https://github.com/vseloved/cl-nlp/.
- abecode 11y agoagreed: I also learned a lot from nltk too, esp. freqdist/probdist as well as the classifiers in nltk and sklearn
- rspeer 11y agoAgreed. NLTK's value is not that it should be your go-to source for NLP algorithms -- when there's a specific task you need to accomplish, there'll be a specific solution by now that works better than NLTK. NLTK's value is that it shows you how to write NLP algorithms, and gives you an understandable starting point when you need to do something that nobody has implemented yet.