Ask HN: Good books/courses for an up-to-date introduction to NLP?
After reading a lot of blog posts about GPT-3 and GPT-2 and not understanding a whole lot other than the fact that the results are _amazing_, I've been wondering if there are any good resources out there for a beginner (someone who's experienced in general software development but has next to no experience in ML, DL, and NLP) looking to get into NLP.
A lot of the books and posts I've found seem to be dated. Are they still good enough to get started with or are there better options?
2 comments
[ 5.6 ms ] story [ 12.3 ms ] threadFor theory on NLP with deeplearning you can follow Stanford course by Christopher Manning.
http://web.stanford.edu/class/cs224n/index.html#coursework
it will give you a good understanding of how deeplearning is used in a certain area of NLP. But remember deeplearning is one of the techniques for solving NLP problems if you are more interested in Understanding NLP then I would recommend the following book.
https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf
Although, Stanford course should give you a great high-level understanding of how GPT models work but if you really need to go under the hood then I would suggest after finishing this course you should learn Unsupervised Learning in DeepLearning.
If it's the first, you should look at HuggingFace, which package transfer learning in a very accessible way to use. But I'd say that's probably too a big leap from no experience at all to that.
I wrote a detailed article on how to get up to speed with NLP - tracing the path I have gone through. My main thing was getting quickly to the point where I could actually use this stuff:
https://towardsdatascience.com/learn-nlp-the-practical-way-b...