- Processed 1000+ text reviews using TF-IDF vectorization with unigrams and bigrams - Applied preprocessing techniques including lemmatization and stopword removal - Trained and evaluated multiple classification models: Naive Bayes, Logistic Regression, SVM, and Random Forest - Compared model performance across different feature representations and reported accuracy metrics Built end-to-end pipeline for text preprocessing, feature extraction, and classification