Backpropagation is so basic in machine learning yet seems so daunting. But actually, it is easier than it seems.

t doesn’t take a math genius to learn Machine Learning (ML). Basically, all you need is college first-year level calculus, linear algebra, and probability theory, and you are good to go. But behind the seemingly-benign first impression of ML, there are a lot of mathematical theories related to ML. For many people, the first real obstacle in learning ML is back-propagation (BP). It is the method we use to deduce the gradient of parameters in a neural network (NN). It is a necessary step in the Gradient Descent algorithm to train a model. Read More