Early Warning System for Student Outcomes
Predictive modeling using California public education data to identify at-risk students and support early intervention decisions.
- Python
- scikit-learn
- XGBoost
- Public Data
A selection of applied data science, machine learning, and data engineering work. Most projects include code, notebooks, and documentation on GitHub.
Predictive modeling using California public education data to identify at-risk students and support early intervention decisions.
Cloud-based predictive analytics to forecast absenteeism and evaluate the ROI of workplace health policies.
Data ingestion, cleaning, and feature engineering pipeline built on public transportation datasets.
NLP-based sentiment and topic analysis comparing online discussions of high- and low-performing school districts.
Comparative modeling of coronary heart disease using expanded clinical features across multiple international patient cohorts.
A reusable Python library for fast, structured exploratory data analysis with consistent reporting patterns.