Backpropagation is one of the primary things one learns when one enters the field of deep learning. However, many people have a shadowy idea of backpropagation as it is explained in many beginner-level courses as an intuitive way of following gradients of the loss function through the layers, but seldom referenced mathematically.
Wherever mathematics is involved (especially in deep learning resources and papers) things get a bit too complex and equations are expected to explain themselves at times. Deep learning nowadays is no longer restricted to students at graduate school or research scholars, but is also explored by undergraduates — who tend to skip the mathematical part as it often seems boring.
