Sentiment Analysis of Amazon Reviews using Deep Learning and NLP Methods

This study explores sentiment analysis of Amazon reviews using NLP and deep learning techniques to understand customer opinions. The main objective is to develop an NLP model using TensorFlow to analyze sentiment in customer reviews. By classifying reviews as positive or negative, the study aims to provide insights into customer satisfaction. The process involves collecting Amazon review data, cleaning the text, and applying deep learning methods to train the model. Various NLP techniques, such as tokenization and word embeddings, help the model understand language patterns. The performance of the model is evaluated to ensure accurate sentiment classification. Challenges like handling sarcasm and ambiguous reviews are considered. The study highlights the importance of deep learning in improving sentiment analysis accuracy. The findings can be useful for businesses to enhance customer experience based on feedback. Future work may explore more advanced techniques or combine text with other forms of data for a more detailed analysis.