AI Engineering/Phase 01/Lesson 05

Chain Rule & Automatic Differentiation

The chain rule is the engine behind every neural network that learns.

Build 1.5 hr Python

Prerequisites: Phase 1, Lesson 04 (Derivatives & Gradients)

#Learning Objectives

Build a minimal autograd engine (Value class) that records operations and computes gradients via reverse-mode autodiff
Implement forward and backward passes through a computation graph using topological sort
Construct and train a multi-layer perceptron on XOR using only the from-scratch autograd engine
Verify autodiff correctness using gradient checking against numerical finite differences

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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.