Neural Networks: Feedforward and Backpropagation Explained

Mathematically, this is why we need to understand partial derivatives, since they allow us to compute the relationship between components of the neural network and the cost function. And as should be obvious, we want to minimize the cost function. When we know what affects it, we can effectively change the relevant weights and biases to minimize the cost function. If you are not a math student or have not studied calculus, this is not at all clear. So let me try to make it more clear. The squished'd' is the partial derivative sign.