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Capitalizing on Unstructured Data with Deep Learning Tools

By   /  May 26, 2016  /  No Comments

unstrby Angela Guess

Ed Burns recently wrote in TechTarget, “At Twitter Inc., Hugo Larochelle’s job is to develop an understanding of how users of the social network are connected to each other and what interests them in order to categorize and promote content that includes tweets, images and videos. To help accomplish that, he and his fellow data analysts use an emerging technology: deep learning tools. As Larochelle, a research scientist at Twitter, explained during a presentation at the Deep Learning Summit in Boston this month, deep learning is a category of machine learning that seeks to understand complex problems, such as interpreting images or text-based natural language. He and other proponents say deep learning techniques — which lean heavily on the use of neural networks — are more useful than traditional machine learning when data analytics applications involve unstructured data or require subjective interpretations.”

Burns goes on, “And deep learning is quickly becoming a hot field in the realm of advanced data analytics. Larochelle said significant advances have been made in deep learning technology and processes over the past five years as researchers and enterprise analytics teams worked to find a good use for all the unstructured text, image and video data they’re now compiling. The availability of robust open source tools has been another key catalyst. Larochelle said his team at Twitter uses Google’s TensorFlow and Torch, an open source machine learning platform developed by researchers at Facebook, Google and Twitter. Such tools have made it easier, he added, for data scientists and other analysts to build deep learning applications. ‘All of these factors combined together have created a perfect storm where deep learning has become very successful in the industry,’ Larochelle said.”

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Photo credit: Flickr/ Rubber Dragon

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