I am constantly amazed by the energy and momentum around data science. Only a few years ago, I would be met with a blank stare when I told someone I planned on going to grad school for machine learning. Today, there is no need for my “it's like computer science, linear algebra, and statistics had a combined love child” analogy as most people instantly respond with “Oh, like AI!”
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A collaborative blog series about collaborative research: a data scientist and a cognitive psychologist combine perspectives.
Dr. Alicia Knoedler: For the past 18 years, I have sought opportunities and means to advocate for researchers working to develop and accelerate their research programs. I had the very fortunate opportunity to meet Dave King in 2014 when he relocated his company to Oklahoma City.
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We recently had to prototype a data application over a supercomputer tuned for graph analysis. We built a proof-of-concept leveraging multiple APIs, Cray’s Urika-GX and Graph Engine (CGE), and a handful of programming languages in less than a week.
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Often times, when we're looking at a mass of data, we're trying to get a sense for relationships within that data. Who is the leader in this social group? What is a common thread between different groups of people? Such relationships can be represented hundreds of ways graphically, but few are as powerful as the classic network diagram.
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Nexflix has collected an impressive amount of data on Hollywood entertainment, made possible by tracking the viewing habits of its more-than 90 million members. In 2013, Netflix took an educated guess based on that data to stream its own original series, risking its reputation and finances in the process. When people were subscribing to Netflix to watch a trove of television series and movies created by well-established networks and studios, why create original content? Now, few would question the move.
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