Blog Post··7 min read
Activation Functions: The Nonlinearity That Makes Neural Networks Work
Without nonlinearity, stacking layers collapses to a single matrix multiplication. Activation functions break that linearity — and the choice of which one determines expressivity, gradient flow, and training efficiency.