Kindle Review Sentiment Analysis

This project analyzes the sentiment of Kindle book reviews using a machine learning model and provides a simple web interface to interact with it.

Features

• Data Cleaning: Preprocesses text data to make it suitable for modeling.
• Feature Extraction: Uses TF-IDF to convert text into numerical vectors.
• Sentiment Prediction: Employs a Naive Bayes classifier to predict if a review is positive or negative.
• Web Interface: Built with Streamlit for easy, interactive use.

How to Run

1. Install the required libraries from requirements.txt.
2. Run the Streamlit app with the command: streamlit run app.py.