Amazon Reviews Sentiment Analysis Overview This project focuses on sentiment analysis of Amazon reviews using machine learning models. The dataset consists of over 17,000 product reviews categorized into Negative, Neutral, and Positive reviews.
Requirements Preprocess the Data: Clean and prepare the dataset. Split the Data: Use 80% for training and 20% for validation. Build Word Embeddings: Convert reviews to sequences and apply padding. Train Models: Implement and train a simple RNN and an LSTM model. Bonus: Predict new reviews and provide a model performance report. Files amazon_reviews.csv: Dataset containing Amazon reviews. main.py: Main script to run the analysis. requirements.txt: List of required Python packages. for more details read assigment pdf