Finding Data for Natural Language Processing

Jayson DeLancey

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29 May 2020CPOL7 min read

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This article is the second in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this article, we'll look at datasets provided by NLTK, as well as an example of capturing your own textual corpus for analysis.

Natural Language Processing needs source data to process. We'll look at some examples, then download some relevant datasets for use in tutorial exercises.

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This article is part of the series 'Sentiment Analysis ◁ Prev View All Next ▷

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Jayson DeLancey

Technical Lead

United States

Jayson manages Developer Relations for Dolby Laboratories, helping developers deliver spectacular experiences with media.

Jayson likes learning and teaching about new technologies with a wide range applications and industries. He's built solutions with companies including DreamWorks Animation (Kung Fu Panda, How to Train Your Dragon, etc.), General Electric (Predix Industrial IoT), The MathWorks (MATLAB), Rackspace (Cloud), and HERE Technologies (Maps, Automotive).

Finding Data for Natural Language Processing

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