Deep learning was recently successfully used in deriving symmetry transformations that preserve important physics quantities. Being completely agnostic. these techniques postpone the identification of the discovered symmetries to a later stage. In this letter we propose methods for examining and identifying the group-theoretic structure of such machine-learned symmetries. https://halohealthcarers.shop/product-category/vitamin-c/