Sentiment-Based-Rating-System
This was my Bachelor final year project after learning the basics of machine learning and natural language processing. While it may not have the most advanced features, I focused on building a robust system that accurately analyzes customer sentiment to assign product ratings.
The system is suitable for businesses looking to gain insights from customer feedback. It processes reviews, detects sentiment, and assigns a corresponding rating, providing valuable information on product performance from the user's perspective.
The project includes a mobile application developed in Java using Android Studio, which allows users to input reviews directly from their devices. Initially, I developed the system using a local setup, and later integrated it with Azure for scalability and improved performance. The project took around 4 months to complete, involving multiple stages of development, testing, and refinement.
Technologies:
- - Android Studio
- - Java (for mobile application)
- - Python
- - Machine Learning
- - Natural Language Processing (NLP)
- - Azure API
Login & Signup
Home Page
Admin Dashboard
Admin Add product
Payment
review Analysis
