  Lecture notes from the course given by Professor Julia Kempe at the summer
school "Statistical physics of Machine Learning" in Les Houches. The notes
discuss the so-called NTK approach to problems in machine learning, which
consists of gaining an understanding of generally unsolvable problems by
finding a tractable kernel formulation. The notes are mainly focused on
practical applications such as data distillation and adversarial robustness,
examples of inductive bias are also discussed.
