Building practical natural language processing systems
summary
Uses Apache OpenNLP to extract information from unstructured Portuguese text (documents, messages, news, social posts). Describes experiments with existing and custom-trained models (including named-entity recognition), model evaluation and tuning techniques, and building NLP enrichment pipelines for real-world applications.
AI-written summary · about
chapters (10)
- 0:00Introduction
- 1:13Motivation
- 7:38Ambiguity
- 11:37Types of capture
- 16:58Types of bodies
- 21:10Tools
- 23:30Models
- 24:55Model creation cycle
- 33:19Using models through the application
- 41:00Closing
related talks
31mNatural Language Processing & Java
17mNatural Language Processing in Automation
06mAdvancements in Natural Language Processing (NLP) and Text Analytics
27mNatural Language Processing with Ruby
55mDemystifying Natural Language Processing across several industry verticals
23mExtracting Entities and Relations in Portuguese Documents
49mDeep Learning Applied to Natural Language Processing (NLP)
30mBuilding Complete State of the art Natural Language Processing