Nothing takes place in the world whose meaning is not that of some maximum or minimum.
—Leonhard Euler
This chapter introduces mathematics essential to understand the basics of neural networks. We emphasize you to not skip this chapter if your mathematical concepts are rusty. You may use this chapter as reference when studying later chapters.
In Section 2.1, we introduce linear algebra which is used to make predictions with the neural network and compute the gradients of the loss function with respect to the neural network which makes learning possible. Efficient implementation of linear ...
