This lecture explores invariance representations for atomistic machine learning, focusing on symmetry functions, permutation invariance, and translation invariance. It covers SOAP, FCHL, Wavelets, and other related concepts, discussing the projection of SO(3) invariant kets and higher-order angular correlations.