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Title: GitHub - MachineLearningReply/pyLDAvis: Python library for interactive topic model visualization. Port of the R LDAvis package.

Open Graph Title: GitHub - MachineLearningReply/pyLDAvis: Python library for interactive topic model visualization. Port of the R LDAvis package.

X Title: GitHub - MachineLearningReply/pyLDAvis: Python library for interactive topic model visualization. Port of the R LDAvis package.

Description: Python library for interactive topic model visualization. Port of the R LDAvis package. - MachineLearningReply/pyLDAvis

Open Graph Description: Python library for interactive topic model visualization. Port of the R LDAvis package. - MachineLearningReply/pyLDAvis

X Description: Python library for interactive topic model visualization. Port of the R LDAvis package. - MachineLearningReply/pyLDAvis

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https://patch-diff.githubusercontent.com/MachineLearningReply/pyLDAvis#pyldavis
R packagehttps://github.com/cpsievert/LDAvis
https://camo.githubusercontent.com/8cea326caa8ed0057d3e65bf51920267edf9edfdb6caa94571890b4e1aecaaee/687474703a2f2f7777772e6b656e6e79736869726c65792e636f6d2f666967757265732f6c64617669732d7069632e706e67
https://pypi.python.org/pypi/pyLDAvis
https://travis-ci.org/bmabey/pyLDAvis
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https://patch-diff.githubusercontent.com/MachineLearningReply/pyLDAvis#installation
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notebook for an overviewhttp://nbviewer.ipython.org/github/bmabey/pyLDAvis/blob/master/notebooks/pyLDAvis_overview.ipynb
documentationhttps://pyLDAvis.readthedocs.org
vignettehttp://cran.r-project.org/web/packages/LDAvis/vignettes/details.pdf
https://patch-diff.githubusercontent.com/MachineLearningReply/pyLDAvis#video-demos
Visualizing Topic Modelshttps://www.youtube.com/watch?v=tGxW2BzC_DU&index=4&list=PLykRMO7ZuHwP5cWnbEmP_mUIVgzd5DZgH
Notebook and visualization used in the demohttp://nbviewer.ipython.org/github/bmabey/hacker_news_topic_modelling/blob/master/HN%20Topic%20Model%20Talk.ipynb
Slide deckhttps://speakerdeck.com/bmabey/visualizing-topic-models
Visualizing & Exploring the Twenty Newsgroup Datahttp://stat-graphics.org/movies/ldavis.html
https://patch-diff.githubusercontent.com/MachineLearningReply/pyLDAvis#more-documentation
the original paperhttp://nlp.stanford.edu/events/illvi2014/papers/sievert-illvi2014.pdf
2014 ACL Workshop on Interactive Language Learning, Visualization, and Interfaceshttp://nlp.stanford.edu/events/illvi2014/
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