Multi-Layer Networks and Forward Pass

#Learning Objectives

• Build a multi-layer network from scratch with Layer and Network classes that perform a complete forward pass
• Trace matrix dimensions through each layer of a network and identify shape mismatches
• Explain how stacking nonlinear activations enables a network to learn curved decision boundaries
• Solve the XOR problem using a 2-2-1 architecture with hand-tuned sigmoid weights