Neural networks · Question 31 of 60
How does a neuron (after the input layer) calculate its activation value?
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Answer
- B Weighted sum of the activations of the previous layer plus its own bias, then passed through a non-linear activation function
Explanation
Each neuron after the input layer first computes a weighted sum of the activation values of all connected neurons in the previous layer, where each connection has its own weight, and adds its bias. This sum is passed through a non-linear activation function. Different activation functions yield different activation values.