"<a href=""https://www.youtube.com/watch?v=gFEE3w7F0ww&amp;t=19m00s"">19:00</a> Thinking in linear algebra terms is super useful! Props to Matlab and other languages that let you program that way.<br><br>The output of a fully-connected neural network layer of n nodes can be thought of as an n-dimensional vector (a matrix of dimension 1*n)", let's call N. Following a previous layer of m nodes, outputting vector M, we know there are m*n connections in total, each with their own weight which could be arranged into an m*n matrix, let's call W. The entire forward propagation step could simply be thought of as N = φ(M * W), where * is the matrix product and φ is the element-wise activation function.,(reply>), @Skippy hey! What did you personally find to be most helpful resource on linear algebra when you were infected by the higher math virus?😄,(reply>), @Skippy I wish I could be better at math. I try but I can't figure out simple stuff sometimes.