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This project performs sentiment analysis on a large dataset of Twitter data, classifying tweets as either positive or negative. The model is trained using logistic regression and leverages Natural Language Processing (NLP) techniques like text preprocessing, TF-IDF vectorization, and stemming to analyze the sentiment of tweets.

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