Which of the following statements about the structure and function of neural networks is true?

The correct answer is B. Training a neural network only changes the values of the weights at the connections between. Section1.7 - Neural Networksof the ISTQB CT-AI syllabus explains that neural networks consist of neurons connected by weighted links. During training,learning occurs by adjusting the weights on these connections. This is the essence of gradient descent and backpropagation…

Machine Learning (ML)

Question

Options

AThe bias of a neuron is determined by the activation values of the neurons in the previous layer
BTraining a neural network only changes the values of the weights at the connections between
CA single-layer perceptron is NOT a neural network
DThe input layer of a deep neural network must have at least as many neurons as its output layer

How the community answered

(28 responses)

A
11% (3)
B
71% (20)
C
4% (1)
D
14% (4)

Explanation

Section1.7 - Neural Networksof the ISTQB CT-AI syllabus explains that neural networks consist of neurons connected by weighted links. During training,learning occurs by adjusting the weights on these connections. This is the essence of gradient descent and backpropagation. Option B correctly states this behavior: only the weights are modified, not the activation functions, neuron counts, or architectural structure.

Topics

#neural network architecture#weights#bias neuron#perceptron

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