Rene Haase

Six ways an ML pipeline fools itself (and the devices that caught them)

I run a nightly pipeline that trains scoring models for sixteen stock chart pattern detectors. It has run nearly 800 times since May 2026, and most of its 88,000 lines of Python are not modelling. The