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Josh Southerland

Josh Southerland

Josh earned his M.S. in Computer Science from the University of Oklahoma in 2012. His education and research experience was focused on the overlap of machine learning and robots. Josh has co-authored many scientific papers in the areas of robotics and brain machine interfaces. He is Exaptive's Machine Learning Lead and helps solve data science challenges for the company and its clients.
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Recent Posts

Machine Learning Helps Humans Perform Text Analysis

The rise of Big Data created the need for data applications to be able to consume data residing in disparate databases, of wildly differing schema. The traditional approach to performing analytics on this sort of data has been to warehouse it; to move all the data into one place under a common schema so it can be analyzed.

This approach is no longer feasible with the volume of data being produced, the variety of data requiring specific optimized schemas, and the velocity of the creation of new data. A much more promising approach has been based on semantic link data, which models data as a graph (a network of nodes and edges) instead of as a series of relational tables.

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