#reproducibility
2 articles
01
·Training & Alignment·★ MEMBER·10 min read
Versioning Data and Models — An Experiment You Cannot Reproduce Never Happened
If you cannot get "92% accuracy" back six months later, it was an anecdote, not an experiment. We build up content-addressing (naming things by their contents), lineage (the graph from inputs to outputs), and the three levels of "how much is worth pinning down" — from the hash math to a manifest you can write today to the mistakes that quietly ruin a year of runs.
02
·Machine Learning Basics·★ MEMBER·10 min read
Data Leakage and Experiment Hygiene — When the Score Is Too Good, Suspect It
When a model scores better than you expected, that is not good news yet. This article splits data leakage into five concrete shapes — outcome-derived columns, preprocessing before the split, time running backwards, duplicates and groups, and a worn-out test set — then covers the detection moves that actually find them and the experiment records that let you dissect the day the number jumped.