Hi guys,
Yesterday I presented at pycon AU on scikit-learn.
The talk went well -- I'm glad I went with the scope I did, and didn't get
too deeply into anything.
In talks afterwards, I found that quite a few people *knew* of
scikit-learn, but few (in this crowd anyway) had actually used it. A slig
Sorry, that sent prematurely.
On Sun, Jul 7, 2013 at 6:58 AM, Joel Nothman
wrote:
> I am not aware of a definitive, complete solution. Lars has built an
> NLTK-compatible classifier interface in nltk.classify.scikitlearn, while
> scikit-learn provides the various components in sklearn.feature_ex
I am not aware of a definitive, complete solution. Lars has built an
NLTK-compatible classifier interface in nltk.classify.scikitlearn, while
scikit-learn provides the various components in sklearn.feature_extraction
that handle text directly, or would allow you to readily produce arrays
from featu
Hi. I’m trying to figure out a good general framework for working with text
(classification and clustering). There is an odd intersection of Python
packages and no clear way to integrate them optimally:
- NLTK seems like the best at handling natural language.
- sklearn has the strongest compon
