December 2025 – Key project milestones and repo hygiene improvements for HWTeng-Teaching/202509-ML-FinTech. Delivered the initial assets import for the U.S. Corporate Bankruptcy Prediction project, performed targeted cleanup of obsolete files and notebooks, and updated the project README. These actions establish a solid base for model development, reduce technical debt, and improve onboarding and maintainability, aligning the repository with governance and future iteration needs.

Monthly performance summary for 2025-11 | HWTeng-Teaching/202509-ML-FinTech. Delivered four data-science notebooks focused on ML prototyping, regression techniques, and statistical analysis, enabling rapid analytics for financial datasets and teaching demonstrations. All work is tracked with explicit commits for reproducibility and traceability across the repository.

October 2025 monthly summary focused on accelerating data readiness for bankruptcy prediction models and increasing maintainability through code cleanup and educational ML assets. Delivered end-to-end data ingestion, preprocessing pipelines, and baseline ML prep; created comprehensive educational notebooks; and reduced technical debt by removing legacy components. Demonstrated strong technical capabilities in data engineering, feature engineering, model prep, and reproducibility. Technologies and skills include Python, pandas, scikit-learn, Jupyter notebooks, and data packaging artifacts. Business value includes faster model turnarounds, higher data quality, and clearer learning materials for the team.

September 2025: Focused on onboarding improvements and data analytics groundwork. Delivered comprehensive repository documentation updates and introduced reproducible data analysis notebooks for College and Boston datasets. No major bugs fixed this month. These efforts improve onboarding efficiency, transparency of project scope, and enable faster data-driven insights for stakeholders.