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Livestream: Organizing Text Data in a Meaningful and Innovative Way
August 30, 2017 @ 9:30 pm - 10:30 pm
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Topic extraction / segmentation has received some attention as a research topic and is an active part of NLP and NLU, however it still has some wrinkles that need to be ironed out before it can reach its potential as a tool for the business world. In any case, with text data being in abundance in a variety of industries, the value of organizing this kind of data in an efficient manner is unquestionable.
In this talk we explore a couple of innovative ways to tackle text data, modeling the whole process as an unsupervised learning problem. The data of this case study stems from a collection of blog posts from over 19K users of Blogger. We have no a priori knowledge of what this corpus is about, so no assumptions about the topic structure are made. Also, the whole process is entirely deterministic.
About the Speaker
Dr. Zacharias Voulgaris was born in Athens, Greece. He studied Production Engineering and Management at the Technical University of Crete, shifted to Computer Science through a Masters in Information Systems & Technology (City University of London), and then to Data Science through a PhD on Machine Learning (University of London). He has worked at Georgia Tech as a Research Fellow, at an e-marketing startup in Cyprus as an SEO manager, and as a Data Scientist in both Elavon (GA) and G2 (WA). He also was a Program Manager at Microsoft, on a data analytics pipeline for Bing. Currently he is the CSO of MAXset LLC and the CTO of a data science startup in London, UK.
Zacharias has authored two other books on data science (through Technics Publications) and several scientific articles. His first book, Data Scientist – The Definitive Guide to Becoming a Data Scientist, has been translated into Korean and Chinese. His second book, Julia for Data Science, was the first book on the topic, and the only book exclusively on Julia published outside the Packt publishing house. He has also reviewed a number of data science books (mainly on Python and R) and had developed a number of new heuristics, functions, and processes for data analytics. Apart from data science, he also has a passion for A.I. technologies, literature, and music.
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