Apparently so; here is a python/cython implementation.
http://rare-technologies.com/deep-learning-with-word2vec-and-gensim/
Dale Smith, Ph.D.
Data Scientist
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From: Fred Mailhot [mailto:fred.mail...@gmail.com]
Sent: Tuesday, June 30, 2015 11:10 PM
To: Mathieu Blondel; scikit-learn-general@lists.sourceforge.net
Subject: Re: [Scikit-learn-general] Library of pre-trained models
Tangent: Are we even allowed to use word2vec anymore, now that Goog has
patented it? (in any case, I'll be looking a bit more closely at GloVe)
F.
On 30 June 2015 at 19:26, Mathieu Blondel
<math...@mblondel.org<mailto:math...@mblondel.org>> wrote:
For unsupervised models that take a long time to train, such as deep learning
or word2vec based feature extractors, this can be pretty useful.
Regardless, a major issue is that we still haven't figured out how to robustly
solve model persistence.
Mathieu
On Wed, Jul 1, 2015 at 4:53 AM, Andreas Mueller
<t3k...@gmail.com<mailto:t3k...@gmail.com>> wrote:
For most applications, this will not work, as the training data needs to come
from the same distribution as your test data.
Language identification is pretty simple, and training a linear classifier on
n-grams should get you quite a bit.
On 06/28/2015 09:58 AM, Erez Segal wrote:
I was searching a library of pre-trained models using scikit-learn (e.g. - a
classifier for language identification),
stored with joblib or something similiar.
Is there such existing library?
Thanks,
Erez
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