NLTK and Machine Learning for Sentiment Analysis

Jayson DeLancey

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29 May 2020CPOL9 min read

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This article is the fifth in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this article we're building an optimized machine learning model.

We’ll introduce some of the Natural Language Toolkit (NLTK) machine learning classification schemes. Specifically, we’ll use the Naive Bayes Classifier to explore applying a feature analysis of movie reviews and learn how to evaluate accuracy.

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

License

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).

NLTK and Machine Learning for Sentiment Analysis

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