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A Feed-Forward Neural Network is a type of Neural Network architecture where the connections are “fed forward”, i.e. do not form cycles (like in recurrent nets).
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The term “Feed forward” is also used when you input something at the input layer and it travels from input to hidden and from hidden to output layer.
The values are “fed forward”.
Both of these uses of the phrase “feed forward” are in a context that has nothing to do with training per se.
- Backpropagation is a training algorithm consisting of 2 steps: 1) Feed forward the values 2) calculate the error and propagate it back to the earlier layers. So to be precise, forward-propagation is part of the backpropagation algorithm but comes before back-propagating.