<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/text-categorization-with-deep-learning-in-r/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/08/text-categorization-deep-learning.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>Given a short review of a product, like &quot;I couldn't put it down!&quot;, can you predict what the product is? In that case it's pretty easy — it's for a book — but this general problem of text categorization comes up in a lot of natural language analysis problems. In his <a rel="nofollow" href="https://blogs.technet.microsoft.com/machinelearning/2017/02/13/cloud-scale-text-classification-with-convolutional-neural-networks-on-microsoft-azure/" target="_blank">talk at useR!2017</a> (shown below), Microsoft data scientist Angus Taylor demonstrates how to build a text categorization model in R. He applies a convolutional neural network (trained using the <a rel="nofollow" href="https://github.com/apache/incubator-mxnet/tree/master/R-package" target="_blank">R interface</a> to the <a rel="nofollow" href="http://mxnet.io/" target="_blank">MXNET </a>deep learning platform) to Amazon review data, and creates a small Shiny app to categorize previously-unseen reviews. The talk also provides an brief introduction to convolutional neural networks and one-hot encoding, if you haven't come across those concepts before.</p>
<p><iframe width="450" allowfullscreen="" src="https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/Deep-Learning-for-Natural-Language-Processing-in-R/player" height="288"></iframe></p>
<p>The model Angus uses in this example is described in more detail in the blog post, <a rel="nofollow" href="https://blogs.technet.microsoft.com/machinelearning/2017/02/13/cloud-scale-text-classification-with-convolutional-neural-networks-on-microsoft-azure/" target="_blank"><em>Cloud-Scale Text Classification with Convolutional Neural Networks on Microsoft Azure</em></a>. If you'd like to implement something similar yourself, you may also want to check out this <a rel="nofollow" href="https://github.com/Azure/Cortana-Intelligence-Gallery-Content/tree/master/Tutorials/Deep-Learning-for-Text-Classification-in-Azure" target="_blank">tutorial on deep learning for text classification</a>, where you can find code and sample data, and explains how to use GPU-accelerated clusters in Azure to speed up the training process. The <a rel="nofollow" href="http://blog.revolutionanalytics.com/2017/06/dsvm-update.html" target="_blank">GPU-enabled Data Science Virtual Machine on Azure</a> contains everything you need to implement the text categorization models described there.</p>
<p>Channel 9: <a rel="nofollow" href="https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/Deep-Learning-for-Natural-Language-Processing-in-R" target="_blank">Deep Learning for Natural Language Processing in R</a></p>
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