Built an end-to-end NLP pipeline to classify text reviews as Positive, Negative, or Neutral. Used NLTK for tokenization and lemmatization, TF-IDF for vectorization, and trained 3 ML classifiers — Logistic Regression, Naive Bayes, and SVM. Visualized sentiment trends and model accuracy using Matplotlib and Seaborn.
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Built an end-to-end NLP pipeline to classify text reviews as Positive, Negative, or Neutral. Used NLTK for tokenization and lemmatization, TF-IDF for vectori...
