Unlock: PDE Fundamentals for Machine Learning

The partial differential equations that appear in modern machine learning: heat and Fokker-Planck for diffusion, continuity for flow matching, Hamilton-Jacobi-Bellman for reinforcement learning, Poisson for score matching. Classification, solution concepts, and where ML actually needs PDE theory versus where it just uses the vocabulary.