Classifying 200k articles in 7 hours using NLP

Post by nl » Wed, Jul 08, 2020, 3:36 AM UTC

jointpdf wrote: post #20

For those interested in related/alternative approaches, one or more of the following established open-source libraries might appeal to you: - Snorkel (training data curation, weak supervision, heuristic labeling functions, uncertainty sampling, relation extraction): https://github.com/snorkel-team/snorkel - AllenNLP (many pretrained NLP research models for tasks beyond text classification, model training and serving,…

Has anyone outside the Snorkel team done anything with it?

I've tried multiple times (although mostly with DeepDive) and it was pretty complicated to get to do anything outside the demos.

The Spacy link is here BTW: https://spacy.io/

Post by kgarten » Wed, Jul 08, 2020, 5:33 AM UTC

whymauri wrote: post #30

kgarten wrote: post #29

Maybe off topic ... Is Stanford ML expert some type of accreditation? How do you become a Stanford ML expert? :) Attending the (excellent) Stanford ML online course on Machine Learning or do I have to read an ML book on Stanford Campus?

They have masters degrees from Stanford. I agree it's a bizarre accredidation since they have a few years of industry experience otherwise, which is, IMO, more relevant.

Agreed. I also value the industry experience more ... I can remember a couple of years ago Stanford faculty complaining at a conference social that they cannot find good candidates for academic positions as Google and Facebook will hire them.

Re: Classifying 200k articles in 7 hours using NLP

Re: Classifying 200k articles in 7 hours using NLP