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💫 Industrial-strength Natural Language Processing (NLP) in Python
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Matthew Honnibal ca7577d8a9 * Allow parsers and taggers to be trained on text without gold pre-processing.
2015-01-30 16:36:24 +11:00
bin/parser * Allow parsers and taggers to be trained on text without gold pre-processing. 2015-01-30 16:36:24 +11:00
docs * Fix quickstart instructions 2015-01-30 10:31:25 +11:00
spacy * Ensure parser and tagger function correctly when training from missing values, indicated by -1 2015-01-30 14:08:56 +11:00
tests * Upd index tests 2015-01-30 12:35:13 +11:00
.gitignore * Ignore cpp files within en dir 2014-12-23 15:19:01 +11:00
.travis.yml * Allow pypy test to fail 2015-01-06 13:13:04 +11:00
dev_setup.py * Upd dev_setup 2015-01-03 21:02:03 +11:00
fabfile.py * Fix clean command 2015-01-25 14:49:29 +11:00
LICENSE.txt * Add license file 2015-01-26 03:07:18 +11:00
README.md Update README.md 2015-01-26 03:03:50 +11:00
requirements.txt * Upd requirements 2015-01-25 23:01:42 +11:00
setup.py * Fix numpy install problem 2015-01-28 13:58:33 +11:00

README.md

spaCy

Fast, state-of-the-art natural language processing pipeline. Commercial licenses available, or use under AGPL.

http://honnibal.github.io/spaCy