This project analyzes customer reviews for skincare products using an unsupervised sentiment analysis model. It includes a web application where users can enter reviews and receive real-time sentiment predictions.
- Automated sentiment analysis for skincare product reviews
- Web application for real-time sentiment classification
- ETL pipeline using Azure Data Factory, Databricks, and Synapse Analytics
- Power BI dashboard for insights and trends
- Azure Data Factory for data ingestion
- Azure Databricks for data processing
- Azure Synapse Analytics for data storage
- Flask for the web application backend
- Power BI for data visualization
- Python 3.12 or higher
- Azure Subscription
- Flask installed
- Azure Data Factory collects raw reviews
- Azure Databricks cleans and transforms data
- Azure Synapse Analytics stores processed data for analysis
A pre-trained unsupervised model predicts whether a review is positive or negative.
Users can submit reviews and receive sentiment predictions instantly.
- Sentiment trends
- Top-rated products
- Review patterns over time
- Create a new branch for your updates
- Test your changes before pushing
- Submit a pull request for review