The document presents an introduction to Hamiltonian Neural Networks, which combines classical mechanics and neural networks to simulate physical systems over time. It covers key concepts, such as Lagrangian and Hamiltonian mechanics, as well as the integration methods relevant to machine learning applications in dynamics. Additionally, it discusses the advantages of using Hamiltonian approaches for better interpretability and energy conservation in simulations.