nlp   28629

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Stop Using word2vec | Stitch Fix Technology – Multithreaded
When I started playing with word2vec four years ago I needed (and luckily had) tons of supercomputer time. But because of advances in our understanding of word2vec, computing word vectors now takes fifteen minutes on a single run-of-the-mill computer with standard numerical libraries1. Word vectors are awesome but you don’t need a neural network – and definitely don’t need deep learning – to find them2. So if you’re using word vectors and aren’t gunning for state of the art or a paper publication then stop using word2vec.

When we’re finished you’ll measure word similarities:

facebook ~ twitter, google, ...

… and the classic word vector operations: zuckerberg - facebook + microsoft ~ nadella

…but you’ll do it mostly by counting words and dividing, no gradients harmed in the making!
nlp  language 
yesterday by jotjotjes
Idioms in sentiment analysis
some nice small datasets for idioms
data  ml  nlp  sentiment 
yesterday by mootPoint

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