Learning

Statistical Physics for Machine Learning Practitioners

Microstates and Macrostates → Stochastic Gradient Descent as Langevin Dynamics

This learning path bridges machine learning and statistical physics, focusing on energy-based models, optimization, and generalization. It builds from foundational statistical mechanics to advanced concepts like free energy and phase transitions, connecting them to modern ML practice.