Data & code toolbox

A set of practical templates and runbooks for data contracts, code style, documentation, and reproducible notebooks to standardize data/code hygiene across teams.

Template

ML experiment notebook template (tracking & reporting)

A practical, copy-ready notebook template with structured experiment metadata, dataset/version provenance, preprocessing and feature records, training and hyperparameter sections, evaluation reporting, model artifact provenance, and a reproducibility checklist — plus guidance for lightweight tracking integrations.

Template
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Runbook

Version control & reproducible workflows runbook

Practical, actionable runbook showing how to version code, analysis notebooks, environments, containers, data, and artifacts so research is auditable and reproducible. Includes example git workflows, notebook practices, environment & container guidance, data-artifact patterns, provenance capture, CI checks, and a reproducibility checklist you can adopt.

Runbook
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