Cross Validation Tutorial

Walk through k-fold experiments leveraging ModularML splitters and experiment tracking. Focus on reproducibility and how to aggregate metrics across folds.

Scenario

Describe the 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.