Natural language processing
It refers all aspects of computational processing, modeling, and analysis of natural language. People sometimes use Natural language understanding to distinguish more sophisticated natural language modeling from other parts of NLP.
Deep learning and Neural network revolutionized NLP.
Topics
- Biomedical natural language processing
- Dialog act
- Lexical feature selection
- Word embedding and Sentence embedding
- Sentiment analysis
- String metric
- Text classification
- Topic model
- Word segmentation
Books
Tools and models
Libraries
- spaCy
- StanfordNLP
- Stanford CoreNLP
- allennlp
- NLTK
- KoNLPy
- http://stackoverflow.com/questions/13466584/korean-language-tokenizer
- Google cloud natural language API
- KenLM
- fastText
- BookNLP
- GluonNLP
Models
- huggingface/pytorch-transformers - A library of state-of-the-art pretrained models for Natural Language Processing (NLP)
- BERT
- GPT
Tutorials and talks
Data
- SQuAD:The Stanford Question Answering Dataset
- http://googleresearch.blogspot.com/2013/12/free-language-lessons-for-computers.html
Courses
- http://see.stanford.edu/see/courseinfo.aspx?coll=63480b48-8819-4efd-8412-263f1a472f5a by Christopher D
- https://www.coursera.org/course/nlp
- CS224d: Deep Learning for Natural Language Processing
- Videos: Natural Language Processing with Dan Jurafsky and Chris Manning, 2012
- Videos: Natural language processing with deep learning (winter 2017)
- YSDA course in Natural Language Processing
- https://phontron.com/class/anlp2022/ by Graham Neubig
- https://www.cs.williams.edu/~kkeith/teaching/f24/cs375/
References
Review
Style
- Success with Style: Using Writing Style to Predict the Success of Novels - can one predict the successful novels just by style and grammar?