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Lessons Learned : Real-life NLP
Submitted by Martin Andrews (@mdda) on Tuesday, 12 July 2016
Building a practical Natural Language Processing system goes far beyond installing an open source toolkit. I will give an overview of some of the components required, and obstacles that have to be overcome for a system that extracts entities and relationships from full-text documents.
- Description of the real-life problem, and the ‘theoretical approach’
- Theory vs Practice - when the 80/20 rule doesn’t work
- Getting a feel for Machine Learning in practice (and saving the day?)
Martin has a PhD in Machine Learning, and has been an Open Source developer since 1999. After a career in finance (based in London and New York), he decided to follow his original passion, and now works on Machine Learning / Artificial Intelligence full-time.