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Softmax cross-entropy forward and backward, then a training loop
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Implement from scratch, with NumPy but no autograd, the forward and backward pass of a softmax layer followed by cross-entropy loss. Keep it numerically stable. Then use it in a small training loop (for example a linear classifier trained with gradient descent) and show the loss going down.
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