Working Groups/Zen of ML: Difference between revisions

// Focus on decision making and identify decisions that arise in building and maintaining machine learning pipelines (from data collection to evaluation)

// Be a useful starting point for beginner pedagogy (both self-learning and teaching)

// Be a useful critical reflection tool to revisit for practitioners

// Language must connect to the technical domain, but remain accessible and comprehensible - i.e. make sense to human beings, minimal jargon

// Be neither a checklist, nor a specification:

// Comprehensive but non-exhaustive

// General, not custom built for specific ML project types.

// What we love

// What we prefer

// If … then …

// Shame on you! (i.e. what we don't like)

// Should not be specific to a particular framework (e.g. PyTorch, Scikit-learn).

// Be as short as possible while being thorough; possible to process at a glance (or three). 18 - 20 short sentences are nice

// Resonate with responsible ML best practice