Introduces Scientific Machine Learning, emphasizing its application in various scientific fields and the connection between machine learning and physics.
Explores atomic descriptors, emphasizing symmetry, locality, and the challenges of incorporating electrostatics in machine learning models for chemistry.
Explores the Bragg-Williams analysis of order-disorder transformations in materials, including enthalpy, entropy, and critical temperature equilibrium.
