Question at position 2 What does backpropagation refer to in neural networks? Computing gradients for all parametersMapping inputs to outputsNormalizing dataUpdating weights in the forward direction

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Question at position 2 What does backpropagation refer to in neural networks? Computing gradients for all parametersMapping inputs to outputsNormalizing dataUpdating weights in the forward direction

BlackTom AI · Accepted Answer

Explore what backpropagation means in neural networks by evaluating each option in turn.
Option 1: 'Computing gradients for all parameters' — This aligns with the core function of backpropagation, which is to compute the partial derivatives of the loss with respect to each parameter in order to update them. The gradient calculations are propagated backward from the output layer to the earlier layers.
Option 2: 'Mapping inputs to outputs' — While neural networks perform input-to-output mappings, backpropagation specifically deals with adjusting parameters using gradients; the mapping itself is achieved during the forward pass, not during backpropagation.
Option 3: 'Normalizing data' — Data normalization is a preprocessing step or a part of input handling, not an operation that backpropagation performs. Backpropagation does not normalize inputs; it computes gradients for learning.
Option 4: 'Updating weights in the forward direction' — Backpropagation involves a backward flow of error information to compute gradients, followed by parameter updates typically performed after the backward pass. The actual weight updates are carried out using those gradients, often in a separate step, and not in the forward direction itself.
By weighing each choice against the role of backpropagation in training neural networks, the option that directly describes the essential computational activity of backpropagation is the one about computing gradients for all parameters.

Question at position 2 What does backpropagation refer to in neural networks? Computing gradients for all parametersMapping inputs to outputsNormalizing dataUpdating weights in the forward direction

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Question at position 2 What does backpropagation refer to in neural networks? Computing gradients for all parametersMapping inputs to outputsNormalizing dataUpdating weights in the forward direction

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