Assertion: neural network's input layer | /r/HasProperty | multiplied by their respective weights
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Source sentences:
text: Similar to the classic perceptron, forward propagation begins with the input values and bias unit from the input layer being multiplied by their respective weights, however, in this case there is a weight for each combination of input (including the input layer’s bias unit) and hidden unit (excluding the hidden layer’s bias unit).