* [Natural Language Processing: An Introduction](https://academic.oup.com/jamia/article/18/5/544/829676) - Oxford

* [Deep Learning for NLP with Pytorch](https://pytorch.org/tutorials/beginner/deep_learning_nlp_tutorial.html)

* [Hands-On NLTK Tutorial](https://github.com/hb20007/hands-on-nltk-tutorial) - NLTK Tutorials, Jupyter notebooks

* [Train a new language model from scratch](https://huggingface.co/blog/how-to-train) - Hugging Face 🤗

* [The Super Duper NLP Repo (SDNLPR)](https://notebooks.quantumstat.com/): Collection of Colab notebooks covering a wide array of NLP task implementations.

* [node-question-answering](https://github.com/huggingface/node-question-answering) - Fast and production-ready question answering w/ DistilBERT in Node.js

* <a id="python"> **Python** - Python NLP Libraries</a> | [Back to Top](#contents)

- [TextAttack](https://github.com/QData/TextAttack) - Adversarial attacks, adversarial training, and data augmentation in NLP

- [TextBlob](http://textblob.readthedocs.org/) - Providing a consistent API for diving into common natural language processing (NLP) tasks. Stands on the giant shoulders of [Natural Language Toolkit (NLTK)](https://www.nltk.org/) and [Pattern](https://github.com/clips/pattern), and plays nicely with both :+1:

- [spaCy](https://github.com/explosion/spaCy) - Industrial strength NLP with Python and Cython :+1:

- [textacy](https://github.com/chartbeat-labs/textacy) - Higher level NLP built on spaCy

- [gensim](https://radimrehurek.com/gensim/index.html) - Python library to conduct unsupervised semantic modelling from plain text :+1:

- [scattertext](https://github.com/JasonKessler/scattertext) - Python library to produce d3 visualizations of how language differs between corpora

- [GluonNLP](https://github.com/dmlc/gluon-nlp) - A deep learning toolkit for NLP, built on MXNet/Gluon, for research prototyping and industrial deployment of state-of-the-art models on a wide range of NLP tasks.

- [AllenNLP](https://github.com/allenai/allennlp) - An NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.

- [PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP) - NLP research toolkit designed to support rapid prototyping with better data loaders, word vector loaders, neural network layer representations, common NLP metrics such as BLEU

- [Rosetta](https://github.com/columbia-applied-data-science/rosetta) - Text processing tools and wrappers (e.g. Vowpal Wabbit)

- [PySS3](https://github.com/sergioburdisso/pyss3) - Python package that implements a novel white-box machine learning model for text classification, called SS3. Since SS3 has the ability to visually explain its rationale, this package also comes with easy-to-use interactive visualizations tools ([online demos](http://tworld.io/ss3/)).

- [jPTDP](https://github.com/datquocnguyen/jPTDP) - A toolkit for joint part-of-speech (POS) tagging and dependency parsing. jPTDP provides pre-trained models for 40+ languages.

- [BigARTM](https://github.com/bigartm/bigartm) - a fast library for topic modelling

- [Snips NLU](https://github.com/snipsco/snips-nlu) - A production ready library for intent parsing

- [Chazutsu](https://github.com/chakki-works/chazutsu) - A library for downloading&parsing standard NLP research datasets

- [Word Forms](https://github.com/gutfeeling/word_forms) - Word forms can accurately generate all possible forms of an English word

- [Multilingual Latent Dirichlet Allocation (LDA)](https://github.com/ArtificiAI/Multilingual-Latent-Dirichlet-Allocation-LDA) - A multilingual and extensible document clustering pipeline

- [NLP Architect](https://github.com/NervanaSystems/nlp-architect) - A library for exploring the state-of-the-art deep learning topologies and techniques for NLP and NLU

- [Flair](https://github.com/zalandoresearch/flair) - A very simple framework for state-of-the-art multilingual NLP built on PyTorch. Includes BERT, ELMo and Flair embeddings.

- [Kashgari](https://github.com/BrikerMan/Kashgari) - Simple, Keras-powered multilingual NLP framework, allows you to build your models in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS) and text classification tasks. Includes BERT and word2vec embedding.

- [Sockeye](https://github.com/awslabs/sockeye) - Neural Machine Translation (NMT) toolkit that powers Amazon Translate.

- [DL Translate](https://github.com/xhlulu/dl-translate) - A deep learning-based translation library for 50 languages, built on `transformers` and Facebook's mBART Large.

- [Jury](https://github.com/obss/jury) - Evaluation of NLP model outputs offering various automated metrics.

- <a id="c++">**C++** - C++ Libraries</a> | [Back to Top](#contents)

- [InsNet](https://github.com/chncwang/InsNet) - A neural network library for building instance-dependent NLP models with padding-free dynamic batching.

- [dfrtopics](https://github.com/agoldst/dfrtopics) - R package for exploring topic models of text.

- [sentiment_classifier](https://github.com/kevincobain2000/sentiment_classifier) - Sentiment Classification using Word Sense Disambiguation and WordNet Reader

- [jProcessing](https://github.com/kevincobain2000/jProcessing) - Japanese Natural Langauge Processing Libraries, with Japanese sentiment classification

- <a id="clojure">**Clojure**</a> | [Back to Top](#contents)

- [Clojure-openNLP](https://github.com/dakrone/clojure-opennlp) - Natural Language Processing in Clojure (opennlp)

- [UBIAI](https://ubiai.tools/) - Easy-to-use text annotation tool for teams with most comprehensive auto-annotation features. Supports NER, relations and document classification as well as OCR annotation for invoice labeling, costs $

- [Shoonya](https://github.com/AI4Bharat/Shoonya-Backend) - Shoonya is free and open source data annotation platform with wide varities of organization and workspace level management system. Shoonya is data agnostic, can be used by teams to annotate data with various level of verification stages at scale.

- [Annotation Lab](https://www.johnsnowlabs.com/annotation-lab/) - Free End-to-End No-Code platform for text annotation and DL model training/tuning. Out-of-the-box support for Named Entity Recognition, Classification, Relation extraction and Assertion Status Spark NLP models. Unlimited support for users, teams, projects, documents. Not FOSS.

- [jieba](https://github.com/fxsjy/jieba#jieba-1) - Python package for Words Segmentation Utilities in Chinese

- [SnowNLP](https://github.com/isnowfy/snownlp) - Python package for Chinese NLP

- [FudanNLP](https://github.com/FudanNLP/fnlp) - Java library for Chinese text processing

- [funNLP](https://github.com/fighting41love/funNLP) - Collection of NLP tools and resources mainly for Chinese

- [python-frog](https://github.com/proycon/python-frog) - Python binding to Frog, an NLP suite for Dutch. (pos tagging, lemmatisation, dependency parsing, NER)

- [SimpleNLG_NL](https://github.com/rfdj/SimpleNLG-NL) - Dutch surface realiser used for Natural Language Generation in Dutch, based on the SimpleNLG implementation for English and French.