In addition to the Deep Learning Workshop I was planning to give at the Fifth Elephant DataScience conference in Bangalore, India (which was attended by more that 1200 developers and data scientists), I was asked to present on a more ‘practical’ topic : I suggested ‘Lessons Learned : Real-life NLP’.
The talk’s motivation is that building a practical Natural Language Processing system goes far beyond installing an open source toolkit.
So the presentation gives 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.
A brief synopsis is :
- 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?)
If there are any questions about the presentation please ask below, or contact me using the details given on the slides themselves.
The presentation was also recorded… and is available via HasGeek YouTube channel. The videos were professionally done, though I can’t vouch for this one, since I can’t bear to watch myself…
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