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Update README.md
fixing small typo
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@ -88,7 +88,7 @@ backPropagate :: forall shapes layers.
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```
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which takes a network, appropriate input and target data, and returns the
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back propagated gradients for the network. The shapes of the gradients are
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appropriate for each layer, and may be trivial for layers like `Rulu` which
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appropriate for each layer, and may be trivial for layers like `Relu` which
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have no learnable parameters.
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The gradients however can always be applied, yielding a new (hopefully better)
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