Natural Language Processing: An Introduction

This talk highlights the importance of text data in data analysis projects, particularly within medical and legal contexts. We’ll highlight sources of text data, explore natural language processing (NLP) tools, and see how the output of NLP can be combined with structured data in psychometric and predictive analytics models. Some highlights of the NLP portion include parsing text data, tagging features (such as parts of speech or named entities), deriving text sentiment using off-the-shelf sentiment tools and derived psychological models, and vectorizing results to integrate with other data sources. Given the importance of integrating text analytics results with other data or within dashboard applications, we’ll take an in-depth look at a few potential next analytics steps once the text data is processed. Finally, a few papers important to text analytics applications will be introduced for listeners who’d like to dive deeper into NLP.

PRESENTER:
Colleen Farrelly, Staticlysm
SESSION ID: 1055
TOPIC: Analytics: Text Analytics
INDUSTRY: Health Care, Legal Services
AUDIENCE: Data Scientist, Epidemiologist, Researcher
SKILL LEVEL: Appropriate for all level

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[tohelpukraine]

Very fascinating and love your AI art .. Thank you

[DanZhukovin]

I'm going to make a mental note to stop disruptive technologies for good, and implement better crime detection systems that don't involve misunderstood intent, context, etc. because frankly, the notion of NLP used has been a service to the short-term, to a few, but to the ruin of many.

[scitechtalktv]

Very good overview of NLP . But I missed the Q&A part of the talk, that is to say: the second half of the video should have questions and answers but for some reason it is not recorded I think

[nofuckingwaythishandleistaken]

I swear I’ve seen this person on Quora.