single neuron computation neural nets foundations
Gradient Descent Algorithm The weights are updated iteratively: \[ w_i := w_i - \eta \frac{\partial L}{\partial w_i} \] \[ b := b - \eta \frac{\partial L}{\partial b} \] where \(\eta\) is the learning rate controlling the step size. Limitations and Solutions