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Combine the forward pass, backpropagation, and data batching into a complete training loop from scratch using only NumPy. Train the model on the scaled wine dataset for quality_binary. Plot the training loss curve and report the final test accuracy.
Combine the forward pass, backpropagation, and data batching into a complete training loop from scratch using only NumPy. Train the model on the scaled wine dataset for quality_binary. Plot the training loss curve and report the final test accuracy.