This workflow automatically analyzes user-submitted product reviews and classifies them by sentiment using OpenAI’s powerful language models. It eliminates the need to manually sift through feedback by tagging each review with a sentiment score.

Developed a comprehensive Sentiment Analysis System aimed at classifying Amazon product reviews into positive, neutral, and negative sentiments. The project leveraged advanced Natural Language Processing (NLP) techniques alongside machine learning algorithms to deliver accurate and actionable insights from customer feedback

Sentiment analysis of The INKEY List skincare reviews from the Sephora dataset using BERT, zero-shot classification, and TF-IDF with logistic regression. This project classifies reviews into positive, negative, or neutral sentiments, offering insights into customer satisfaction.

Sentiment analysis of The INKEY List skincare reviews from the Sephora dataset using BERT, zero-shot classification, and TF-IDF with logistic regression. This project classifies reviews into positive, negative, or neutral sentiments, offering insights into customer satisfaction.