| | Output | | --- | --- | | Neuron 1 | 0.7 | | Neuron 2 | 0.3 | | Bias | 0.2 |
For example, for Neuron 1:
| | Neuron 1 | Neuron 2 | Output | | --- | --- | --- | --- | | Input 1 | | | | | Input 2 | | | | | Bias | | | | build neural network with ms excel new
| | Neuron 1 | Neuron 2 | Output | | --- | --- | --- | --- | | Input 1 | 0.5 | 0.3 | | | Input 2 | 0.2 | 0.6 | | | Bias | 0.1 | 0.4 | | Calculate the output of each neuron in the hidden layer using the sigmoid function: | | Output | | --- | --- | | Neuron 1 | 0
output = 1 / (1 + exp(-(weight1 * input1 + weight2 * input2 + bias))) build neural network with ms excel new