Created a sentiment analysis system to classify hospital patient feedback as Positive, Negative, or Neutral. • Used NLP tools including NLTK, TF-IDF Vectorization, and VADER Sentiment Analyzer. • Balanced training data with SMOTE and fine-tuned model using RandomForest Regressor. • Integrated model outputs with a MySQL database for real-time feedback analysis. • Results presented in an analytics dashboard with Power BI visualizations.