| Project | What I did |
|---|---|
| π’ IBM / mcp-context-forge | Removed legacy CSRF endpoint Β· standardized cookie naming across the Python backend (Merged PR #4936) |
| π§ͺ IBM / mcp-context-forge | Boosted React UI test coverage from 66.93% β 98.24% across all metrics (Merged PR #4764) |
|
Production-grade EDA library β C++17 core with Python bindings via nanobind. Ships native wheels for Windows, macOS & Linux across Python 3.9β3.12. Streams 2M rows in 23 seconds at O(1) memory using Welford stats + HyperLogLog + stratified Parquet sampling. |
End-to-end fraud detection on severely imbalanced data β ROC-AUC 0.991 Β· PR-AUC 0.999 using Random Forest with stratified cross-validation. 20+ behavioral features + SHAP explainability + risk scoring system (0β100) for non-technical stakeholders. |
|
Automated RFM pipeline over 1M+ transaction records with K-Means clustering into 4 customer personas β what took days now runs in minutes. XGBoost churn classifier + live Streamlit CRM dashboard with AI-predicted churn probabilities for targeted marketing campaigns. |
|


