Curious about techniques and methods for applying data science to unstructured text? Join us at the DC NLP February Meetup!
This month, we’re featuring a single speaker with a presentation related to sentiment analysis:
Nathan Danneman received his PhD in political science from Emory University, with focuses in international conflict and applied statistics. He currently works as a Data Scientist at Data Tactics, where he works on a range of topics including geospatial analysis, outlier detection, and text analysis. He will present Item Response Theory models as a means of unsupervised sentiment analysis.
The DC NLP meetup group is for anyone in the Washington, D.C. area working in (or interested in) Natural Language Processing. Our meetings will be an opportunity for folks to network, give presentations about their work or research projects, learn about the latest advancements in our field, and exchange ideas or brainstorm. Topics may include computational linguistics, machine learning, text analytics, data mining, information extraction, speech processing, sentiment analysis, and much more.
For more information and to RSVP, please visit: http://www.meetup.com/
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