Short write-ups on the parts of ML that decide whether a model gets used: calibration, leakage, explanation, reporting. Plus what I am learning as I move into LLM systems.
// status
The first posts are being written.
Two are drafted: one on calibration in clinical risk models, one on moving from classical ML into LLM systems. They go up once they are reviewed.