Reproducibility
Reproducibility in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
From notebook to reproducible run
Use from notebook to reproducible run to move the engineering foundations production brief toward a defensible release.
Engineering foundationsContracts before models
Use contracts before models to move the engineering foundations production brief toward a defensible release.
Engineering foundationsTraining code is product code
Use training code is product code to move the engineering foundations production brief toward a defensible release.
Engineering foundationsContainers and configuration without surprises
Use containers and configuration without surprises to move the engineering foundations production brief toward a defensible release.
Engineering foundationsObservable, idempotent, failure-safe workflows
Use observable, idempotent, failure-safe workflows to move the engineering foundations production brief toward a defensible release.
Engineering foundationsRead a research paper as an executable specification
Turn a research paper into a testable claim map, implementation contract, and prioritized reading plan before writing code.
Engineering foundationsReproduce, validate, and productionize a paper
Implement a paper from baseline to novel component, diagnose reproduction gaps, and adapt it for production without silently changing its claim.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.
The winding road through TFX and Kubeflow
Platform adoption is a product and socio-technical problem.
Netflix · Data & platformMetaflow: a human-centric path from notebook to production
The best abstraction preserves the user’s reasoning model while adding production guarantees.