Processing unstructured text data at scale has largely been a challenge from both an algorithm and an engineering perspective. However, the advent of cloud computing solved most off the difficulties in building scalable algorithms for text analytics. Arun Veettil shares his experience and lessons learned developing a customized, enterprise-level NLP platform to replace a leading text analytics vendor platform.
Arun Veettil is the chief architect at Skellam AI, a company dedicated to helping businesses develop custom AI solutions. Arun is a tech veteran with over 17 years of industry experience. For the last seven years, Arun has been working at the intersection of machine learning and product development. Previously, he worked at Point Inside, Nordstrom Advanced Analytics, the Walt Disney Company, and IBM. His expertise includes developing machine learning algorithms to run against very large amounts of data and building large-scale distributed applications. Arun holds a master’s degree in computer science from the University of Washington and a bachelor’s degree in electronics engineering from the National Institute of Technology, Allahabad, India.
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