Transfer Learning Tutorial

Fine-tune a pretrained backbone by freezing/unfreezing nodes and swapping FeatureSets. Covers best practices for optimizer resets and loss weighting.

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.