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How we built Tagger News: machine learning on a tight schedule

71 pointsby var_explainedabout 8 years ago

2 comments

minimaxirabout 8 years ago
Link to original HN submission: <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=14337275" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=14337275</a><p>It&#x27;s worth noting for future reference that in terms of supervised learning of labels given a text document input, fasttext (<a href="https:&#x2F;&#x2F;github.com&#x2F;facebookresearch&#x2F;fastText" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;facebookresearch&#x2F;fastText</a>) is <i>leagues</i> ahead of conventional approaches in both accuracy and training speed, and there is a Python interface (<a href="https:&#x2F;&#x2F;github.com&#x2F;salestock&#x2F;fastText.py" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;salestock&#x2F;fastText.py</a>) for use with Django&#x2F;Flask (unfortunately, recent fasttext changes have broken the interface for now).
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_ehtabout 8 years ago
I noticed some things were pretty terribly tagged earlier this week. Robots have a ways to go, this is good news.