NLP Learning Resources in 2020
There’s a lot of great freely available resources in NLP right now; and the field is moving quickly with the recent success of neural models. I wanted to mention a few that look interesting to me.
Jurefsky and Martin’s Speech and Language Processing
The third edition is a free ebook that is in progress that covers a lot of the basic ideas in NLP. It’s got a great reputation in the NLP community and is nearly complete now. It makes a good starting point or reference book for a particular subject.
Stanford CS224n: NLP with Deep Learning
This course covers Deep Learning from NLP in Pytorch and the 2019 video lectures are great. It’s run by Chris Manning who is a leader in the field of neural chunking and parsing, and for example guided Stanza.
fast.ai NLP Course
This is a lot less academic than other approaches, which gives a good contrast, in their library over Pytorch. Lectures available online; they also cover some NLP in the general fast.ai course.
Notable free resources
These all look good, but I would start with the above 3.
- Coursera NLP specialisation from deeplearning.ai in Tensorflow
- Training transformer from Huggingface with very popular transformer library
- NLTK Book good for the foundations in Python
- Yandex NLP Course including 2019 Jupyter notebooks (English), slides and lectures (Russian)
- CMU 2017 Neural NLP
- Oxford 2017 Deep NLP
- Eistenstein’s NLP notes - very detailed!
- Various NLP Colab Notebooks
Also most Deep Learning courses will tend to touch on NLP, such as NYU 2020 Deep Learning with Pytorch.
Resource Resources
Almost all of these and more can be found at Awesome NLP and Awesome Deep Learning for NLP; they’re probably more up to date too.