Change back-propagation to backpropagation
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@ -790,8 +790,7 @@ and updating the weights within the network is it possible to gain
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experience $E$ at carrying out a task $T$. How the weights are updated
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depends on the algorithm which is used during the \emph{backward pass}
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to minimize the error. This type of procedure is referred to as
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\emph{back-propagation} (see
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section~\ref{ssec:theory-back-propagation}).
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\emph{backpropagation} (see section~\ref{ssec:theory-backprop}).
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One common type of loss function is the \gls{mse} which is widely used
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in regression problems. The \gls{mse} is a popular choice because it
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