NLP in Data Science MD

P.S.: this blog entry is long overdue.

On June 16, there was an event held by Data Science MD on natural language processing (NLP). The first speaker was Brian Sacash, a data scientist at Deloitte, and his talk was titled NLP and Sentiment Analysis, which is a good demonstration on the Python package nltk, and its application on sentiment analysis. His approach is knowledge-based, and its quite different from the talk given by Michael Cherny, as presented in his talk in DCNLP and his blog. (See his article.) Brian has a lot of demonstration codes in Jupyter notebook in his Github.

The second speaker was Dr. Daniel Russ, a staff scientist at National Institutes of Health (NIH) and my colleague. His talk was titled It Takes a Village To Solve A Problem in Data Science, stressing the amount of brains and powers involved in solving a data science problem in businesses. He focused on the SOCcer project, (see a previous blog post) which I am also a part of the team, and also the interaction with Apache OpenNLP project. (Slideshare: It Takes a Village To Solve A Problem in Data Science from DataScienceMD)

  • Data Science MD. [Meetup]
  • Brian Sacash, “Introduction to NLP.” on his Github: bsacash/Introduction-to-NLP. [Github]
  • Brian Sacash. [bsacash]
  • Natural Language Toolkit: nltk. [nltk]
  • Dr. Daniel Russ. [NIH]
  • SOCcer. [NIH]
  • OpenNLP. [Apache]
  • Daniel Russ, Kwan-yuet Ho, Melissa Friesen, It Takes a Village To Solve A Problem in Data Science. [Slideshare]
  • Kwan-Yuet Ho, “SOCcer: Computerized Coding in Epidemiology,” Everything in Data Analytics, WordPress (2016). [WordPress]

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