This repo, is part of my notes from the udemy course "Machine Learning: Natural Language Processing in Python (V2)". The word-to-vector transformation methods are compared for their accuracy in a given dataset. Four methods used to transform word-to-vectors are Stopwords, simple_tokenizer, LemmaTokenizer and StemTokenizer.
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Comparing the word-to-vector transformation methods for their accuracy in a given dataset
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