The Math Behind Deep Learning
In this chapter, we discuss the math behind deep learning. This topic is quite advanced and not necessarily required for practitioners. However, it is recommended reading if you are interested in understanding what is going on under the hood when you play with neural networks.
Here is what you will learn:
- A historical introduction
- The concepts of derivatives and gradients
- Gradient descent and backpropagation algorithms commonly used to optimize deep learning networks
Let’s begin!
