Lesson 13: Deep Learning Foundations to Stable Diffusion

(All lesson resources are available at http://course.fast.ai.) In this lesson, we dive into backpropagation and the creation of a simple Multi-Layer Perceptron (MLP) neural network. We start by reviewing basic neural networks and their architecture, then move on to implementing a simple MLP from scratch. We focus on understanding the chain rule and backpropagation in the context of neural networks, and demonstrate how to calculate derivatives using Python and the SimPy library.

We also discuss the importance of the chain …

derivatives discuss error explore floating point functions gradient importance linear math mean process pytorch relu trick