Learning the right values for weights and thresholds is essential for good activation rules that lead to accurate predictions. In addition, a neural network’s other parameters also require tuning, such as the number of hidden layers and number of neurons within each layer. To optimize these parameters, gradient descent (see Chapter 6.3) could be used.
