We will review reinforcement learning methods for mean field models, both in the cooperative (mean field control) and non-cooperative (mean field game) settings. After presenting general heuristics, we will focus on a few specific algorithms for which convergence has been rigorously proved. We will then provide numerical illustrations on several examples borrowed from the literature.