Technical
Technical notes
Technical notes on machine learning, artificial intelligence, model testing, and financial applications.
ML/AI
Testing ML models
How to evaluate models beyond headline accuracy.
Practice
Model documentation
What should be recorded about assumptions, data, intended use, and limitations.
Cloud
Cloud architecture for model systems
How modern model systems depend on data pipelines, infrastructure, monitoring, and governance.
Finance
AI in accounting and finance
Where AI systems affect accounting, reporting, forecasting, audit, and decision support.
Interpretation
Explainability and limits
Why explanations are useful, but not the same as proof.
These notes are educational. They are not personal financial, investment, legal, or tax advice.