Evaluation
Evaluation in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Prompt, retrieve, adapt, train, or buy?
Use prompt, retrieve, adapt, train, or buy? to move the foundation models production brief toward a defensible release.
Foundation-model lifecycleCorpus provenance, mixtures, and decontamination
Use corpus provenance, mixtures, and decontamination to move the foundation models production brief toward a defensible release.
Foundation-model lifecyclePretraining objectives, scaling, and checkpoints
Use pretraining objectives, scaling, and checkpoints to move the foundation models production brief toward a defensible release.
Foundation-model lifecycleSFT, preference optimization, safety, and tools
Use sft, preference optimization, safety, and tools to move the foundation models production brief toward a defensible release.
Foundation-model lifecycleEvals, model cards, feedback, and reproducibility
Use evals, model cards, feedback, and reproducibility to move the foundation models production brief toward a defensible release.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.