Checkpointing Tutorial

Demonstrate saving experiment state (models, optimizers, FeatureSets) and resuming mid-training. Highlight serialization policies, artifact layout, and failure recovery.

Scenario

Describe the business or research question being addressed and why this workflow matters.

Setup

Outline dataset prep, FeatureSet definitions, and experiment context initialization.

Training

Demonstrate how to assemble nodes, losses, optimizers, and training phases for this scenario.

Evaluation

Summarize metrics, qualitative checks, and how to inspect :class:LossRecord outputs.

What’s Next

Link to relevant how-to guides, explanations, or follow-up tutorials.