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Shakespearean language preprocessing pipeline

Over at PyBooks, the team wants to transform a vast library of Shakespearean text data for further analysis. The most efficient way to do this is with a text processing pipeline, starting with the preprocessing steps.

The following have been loaded for you: torch, nltk, stopwords, PorterStemmer, get_tokenizer.

The Shakespearean text data is saved as shakespeare and the sentences have already been extracted.

This exercise is part of the course

Deep Learning for Text with PyTorch

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create a list of stopwords
stop_words = set(____(____))
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