CompTIA
DY0-001 · Question #79
Which of the following explains back propagation?
The correct answer is D. The passage of errors backward through a neural network to update weights and biases. Back propagation computes the gradient of the loss (error) with respect to each weight by propagating the error signal backward through the network, then uses those gradients to adjust weights and biases.
Machine Learning
Question
Which of the following explains back propagation?
Options
- AThe passage of convolutions backward through a neural network to update weights and biases
- BThe passage of accuracy backward through a neural network to update weights and biases
- CThe passage of nodes backward through a neural network to update weights and biases
- DThe passage of errors backward through a neural network to update weights and biases
How the community answered
(30 responses)- A3% (1)
- C7% (2)
- D90% (27)
Explanation
Back propagation computes the gradient of the loss (error) with respect to each weight by propagating the error signal backward through the network, then uses those gradients to adjust weights and biases.
Topics
#backpropagation#neural network#weight update#error propagation
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