Brain
- auditory cortex
- somatosensory cortex
NN Model
Neuro.IO
Dentrite => Axon
input layer > hidden layer (intermediate layer) > output layer
all hidden layer nodes are called “activation units”
$$a_i^{(j)} = \text{“activation” of unit $i$ in layer $j$}$$ $$\Theta^{(j)} = \text{matrix of weights controlling function mapping from layer $j$ to layer $j+1$}$$
Forward Propagation
using trained parameters $\theta_{n}$ we can predict the output by calculate the output layer value