Lesson 3: Training, Experiment Tracking, and Model Evaluation

Build a guided MATLAB exercise covering training options, optimizers, learning rates, and mini-batches.
Apply custom training-loop concepts to a practical engineering or data scenario.
Validate results and troubleshoot an issue involving saving checkpoints and selecting the best model.

Explain and apply training options, optimizers, learning rates, and mini-batches.
Use experiment manager and hyperparameter comparison in a structured workflow.
Validate outputs with plots, metrics, tests, or simulation evidence.

Lesson Overview