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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/07/neural-embeddings-nlp.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>At the useR!2017 conference earlier this month, my colleague Ali Zaidi <a rel="nofollow" href="https://user2017.sched.com/event/Axpk/neural-embeddings-and-nlp-with-r-and-spark?iframe=no&w=&sidebar=yes&bg=no" target="_blank">gave a presentation</a> on using <a rel="nofollow" href="http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/" target="_blank">Neural Embeddings</a> to analyze <a rel="nofollow" href="https://github.com/Microsoft/ghinsights" target="_blank">GitHub pull request comments</a> (processed using the tidy text framework). The data analysis was done using R and distributed on Spark, and the resulting neural network trained using the <a rel="nofollow" href="https://github.com/Microsoft/CNTK" target="_blank">Microsoft Cognitive Toolkit</a>. You can see the slides here, and you can <a rel="nofollow" href="https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/Neural-Embeddings-and-NLP-with-R-and-Spark%5C" target="_blank">watch the presentation</a> below. </p>
<p><iframe width="450" allowfullscreen="" src="https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/Neural-Embeddings-and-NLP-with-R-and-Spark/player" height="288"></iframe></p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://blog.revolutionanalytics.com/2017/07/neural-embeddings-nlp.html"> Revolutions</a></strong>.</div>
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