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This comment is funny, and also unfortunate. Overall, the article gives a broad overview of a typical NLP pipeline, and demonstrates the concepts with a neat example. Sure it could be improved, but it seems that you interpreted the fact that it can be improved as a sign that it's almost entirely unhelpful. In what world is that mindset useful?

For the example task in the article (classifying whether a tweet is about disasters), it would be genuinely surprising if `@` mentions were meaningful. Sure, this would be something you would investigate, but the general idea of `removing words that are not relevant` as a pre-processing step is definitely not bad advice.




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