Deep neural network notation

The explanation of the notation is as follows:

  • l: Number of layers is 4
  • n[l]: Number of nodes in layer

For the following architecture, this is as follows:

  • n [0]: Number of nodes in input layer, that is, 3
  • n [1]: 5
  • n [2]: 5
  •  n [3]: 3
  • n [4]: 1
  • [l]: Activations in layer l:

As we already know, the following equation goes through the layers:

z = wTX + b

Hence, we get the following results:

  •  Activation: a = σ(z) 
  • w[l]: Weight in layer l
  • b[l]: Bias in layer l
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