Product Review Classification

Team Members:

• Dhanavikram Sekar
• Hariharan Kumar
• Naveen Vinayaga Murthy

Project Overview

This project focuses on extracting valuable insights from the abundance of textual consumer feedback available for a certain category of products in Amazon’s e-commerce website. The technical objective of this project is to develop a robust machine learning model that can efficiently classify product reviews into positive, negative, and neutral sentiments using Sentiment Analysis and Natural Language Processing techniques.

Files in the Repository

1. Data:
   • data: Folder containing dataset used for this project.
2. Code:
   • data_read.py: Contains utilities that can be used to download and/or read the data.
   • pre_process.py: Contains utilities that help in preprocessing the textual data.
   • model.py: Comprises of functions required to train and evaluate the model.
   • main.ipynb: Contains execution of the project, with processes like Data Pre-processing, Analysis, Vectorization and Modelling.

Note: Create a virtual environment and install all the required packages from requirements before running the code.