data-disasters

Simple things that are hard and important

How metric definitions, ambiguous calculations, sample sizes, and domain knowledge make calculating a humble average a formidable and thought-deserving task

Why machine learning hates vegetables

A personal encounter with 'intelligent' data products gone wrong