In this project I Preprocess the movie dataset into a more convenient format, and then transform them into feature vector through CountVectorizer then Assessed word relevancy via term frequency-inverse document frequency i ALSO TRIED hashing vectorizer for memory efficienct on large data and using SDG CLASSIFER
nltk logistic-regression latent-dirichlet-allocation countvectorizer stemming-porters frequency-inverse-document-frequency sdgclassifier hashingvectorizer
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Updated
Apr 28, 2026 - Jupyter Notebook