How to: Natural Language Processing
_Libraries for working with human languages._

- General
  - [gensim](https://github.com/RaRe-Technologies/gensim) - Topic Modeling for Humans.
  - [langid.py](https://github.com/saffsd/langid.py) - Stand-alone language identification system.
  - [nltk](http://www.nltk.org/) - A leading platform for building Python programs to work with human language data.
  - [pattern](https://github.com/clips/pattern) - A web mining module.
  - [polyglot](https://github.com/aboSamoor/polyglot) - Natural language pipeline supporting hundreds of languages.
  - [pytext](https://github.com/facebookresearch/pytext) - A natural language modeling framework based on PyTorch.
  - [PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP) - A toolkit enabling rapid deep learning NLP prototyping for research.
  - [spacy](https://spacy.io/) - A library for industrial-strength natural language processing in Python and Cython.
  - [Stanza](https://github.com/stanfordnlp/stanza) - The Stanford NLP Group's official Python library, supporting 60+ languages.
- Chinese
  - [funNLP](https://github.com/fighting41love/funNLP) - A collection of tools and datasets for Chinese NLP.
  - [jieba](https://github.com/fxsjy/jieba) - The most popular Chinese text segmentation library.
  - [pkuseg-python](https://github.com/lancopku/pkuseg-python) - A toolkit for Chinese word segmentation in various domains.
  - [snownlp](https://github.com/isnowfy/snownlp) - A library for processing Chinese text.