Amazon Reviews for Sentiment Analysis

In my project on Amazon Reviews Sentiment Analysis, I developed a logistic regression model using natural language processing techniques to classify the sentiment of Amazon product reviews as positive or negative. Leveraging the Amazon Fine Food Reviews dataset, I performed data preprocessing, including HTML tag removal and tokenization, before vectorizing the text data using CountVectorizer. Through hyperparameter tuning and rigorous evaluation using metrics such as accuracy, F1-score, and ROC AUC score, the model demonstrated robust performance in sentiment classification. By interpreting the model's coefficients, I gained insights into the key features driving positive or negative sentiment in Amazon reviews. This project showcases the potential of sentiment analysis to extract valuable insights from customer feedback, empowering businesses to make data-driven decisions for product enhancement and customer satisfaction improvement.

[@hammad.xhafique]

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