Save, Load, and Export Keras Models the Right Way

Clear, hands-on guide to Keras v3 saving: use the unified .keras format to store architecture, weights, compile state, and optimizer; load with keras.models.load_model. Handle custom layers/functions via @register_keras_serializable, custom_objects, or custom_object_scope. Serialize configs with get_config/from_config, clone models, and save or transfer only weights when needed. For serving, export a lightweight SavedModel with model.export() or customize endpoints via ExportArchive. (Requires Keras ≥ 2.13; content adapted under CC BY 4.0.)