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* Upd index.rst

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Matthew Honnibal 2015-01-25 23:38:36 +11:00
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@ -24,7 +24,9 @@ little in the last ten years. In academia, it's changed entirely. Amazing
improvements in quality. Orders of magnitude faster. But the
academic code is always GPL, undocumented, unuseable, or all three. You could
implement the ideas yourself, but the papers are hard to read, and training
data is exorbitantly expensive. So what are you left with? NLTK?
data is exorbitantly expensive. So what are you left with? A common answer is
NLTK, which was written primarily as an educational resource. Nothing past the
tokenizer is suitable for production use.
I used to think that the NLP community just needed to do more to communicate
its findings to software engineers. So I wrote two blog posts, explaining