Getting Started with Natural Language Processing: US Airline Sentiment Analysisby@comet.ml
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Getting Started with Natural Language Processing: US Airline Sentiment Analysis

November 10th 2019
11 min
by @comet.ml 1,062 reads
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We’re going to build a model that tries to predict the sentiment (positive, neutral, or negative) of tweets relating to US Airlines, using the popular Twitter US Airline Sentiment dataset. We use standard NLP preprocessing techniques such as tokenization, stopword removal, and stemming. We also use Comet for experiment management, visualizations, code tracking and hyperparameter optimization. We're going to focus on NLP-specific analysis in this write-up, but there are excellent sources of further feature engineering and exploratory data analysis.

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