Continuing our whirlwind tour of the DC area, this month we'll be meeting at WeWork Dupont Circle, right off the red line (location has been updated from Shaw). Come check out an exciting talk about the intersection of NLP and information retrieval in a cool co-working space!
Doug Turnbull is a Search Relevance Consultant at OpenSource Connections and author of the Manning book Relevant Search (currently available for pre-order on Amazon). He crafts search & recommendation solutions using Solr/Elasticsearch, sprinkling a little natural language processing and machine learning on top for good measure. Doug's solutions make a big difference for companies like O'Reilly Media and Advance Auto Parts. His secret weapon is enabling non-technical product owners, businesses, and domain experts to take deeper control of their search. Through writing and speaking, Doug wants to humanize search and recommendations, making these topic less intimidating for everyone: developers, non-technical folks, and users alike. Doug loves building tools to help with search relevancy, including Quepid, Splainer and Elyzer.
In this talk, you'll get an overview of search engine internals and learn how to turn Elasticsearch into a smart comparison powerhouse for your organization. Far more than just a full-text search engine, Elasticsearch can be 'taught' to detect at-risk students, predict the weather, and find similar images at high scale.
We'll gather starting at 6:30pm at WeWork Wonder Bread Factory. Introductions & announcements will start around 7:00pm, and presentations will begin at 7:30pm. Afterwards, there will be plenty of time for follow-up questions, networking, and more.
DC NLP meets each month to network, socialize, and learn about the interesting work folks are doing in natural language processing, computational linguistics, text analytics, and more.
Do you have something you'd like to share with the group? Let us know! We're always looking for speakers to give talks at future meetups, and don't forget to follow @DCNLP on Twitter!