[Refactor] : Iris classification demo into sine wave regression #42
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This refactor shifts the example from a classification task on the Iris dataset to a regression-style task on noisy sine wave data. The model architecture has been expanded with an extra hidden layer, ELU activations, and an Adam optimizer with gradient clipping. The training loop is now longer with a manual LR scheduler, and the loss function blends Huber + MAE for more robust regression.
Overall, this makes the demo more representative of regression workflows and adds numerical stability