Building Reliable ML Evaluation Loops
Notes on designing model evaluation workflows that stay useful after deployment.
Reggie
Machine Learning Engineer & Data Scientist
What I Track Before Shipping a Model
A practical checklist for data quality, monitoring, and production readiness.
Production Forecasting Pipeline
End-to-end forecasting system with automated feature generation and drift checks.
Experimentation Dashboard
Interactive analytics for monitoring A/B tests and explaining metric movement.
Pragmatic MLOps for Small Teams
A talk on lightweight workflows for model deployment, monitoring, and iteration.
Interpretable Models in Product Decisions
Examples of using model explanations to help teams make better decisions.
About
I build reliable machine learning systems and data products, from experimentation and model development to deployment, monitoring, and iteration in production.
Expertise
- Applied machine learning and predictive modeling
- Statistical analysis, experimentation, and A/B testing
- Data pipelines, feature engineering, and MLOps workflows