Research Focus
Researched evolutionary genetic algorithms for association rule extraction, applied to customer profiling. The aim was to analyze contracting trends and identify cross-sell opportunities for a real business partner.
What I Built
The main contribution was a custom algorithm based on binary logic for processing large volumes of customer data with association rules. There was no existing library that matched the approach, so I built the core logic from scratch.
I also implemented data anonymization techniques to handle the sensitivity of the customer data while keeping the analytical results meaningful.
Key Achievements
- Created a novel binary logic algorithm for massive customer data processing
- Delivered research with direct business applications for customer profiling
- Built ML algorithms from first principles without dedicated libraries
- Protected sensitive data through comprehensive anonymization techniques