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

Re:How we built Tagger News: machine learning on a tight sch... by snissn on Monday May 22, 2017 @03:16PM (#14396165)

Can you suggest any unsupervised learning? I want to take a body of text associated with users and come up with keywords/topics with each user. Thanks! :)

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Re:How we built Tagger News: machine learning on a tight sch... by capybara on Monday May 22, 2017 @03:50PM (#14396401)

Some fairly widely-used techniques include LSI, LDA, and word2vec or doc2vec. There a lot of different techniques out there! I'm one of the creators of Tagger News, and we used LDA with python's Gensim package. Here's a good tutorial: https://radimrehurek.com/gensim/tut2.html

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Re:How we built Tagger News: machine learning on a tight sch... by minimaxir on Monday May 22, 2017 @03:53PM (#14396431)

Note that fasttext is the next generation of word2vec/doc2vec, and shares many of the same creators.

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