Archived
Shopping Pattern Analyzer
Data-driven application using the Apriori Algorithm to analyze customer shopping frequencies and repetitions.
PythonReactDocker
Overview
This project was an exploration into Data Mining techniques. The goal was to build a tool that could ingest thousands of CSV transaction records and output logical item-set rules (e.g., If a customer buys Bread and Milk, they have an 80% chance of buying Butter).
Technical Implementation
The Apriori algorithm was optimized in Python to handle large datasets efficiently. A React frontend allows users to upload datasets securely, adjust minimum support/confidence thresholds dynamically, and visualize the generated rules via data tables. The entire tool is containerized using Docker for zero-configuration deployments.