  We survey some recent applications of machine learning to problems in
geometry and theoretical physics. Pure mathematical data has been compiled over
the last few decades by the community and experiments in supervised,
semi-supervised and unsupervised machine learning have found surprising
success. We thus advocate the programme of machine learning mathematical
structures, and formulating conjectures via pattern recognition, in other words
using artificial intelligence to help one do mathematics.
  This is an invited chapter contribution to Elsevier's Handbook of Statistics,
Volume 49: Artificial Intelligence edited by S.~G.~Krantz, A.~S.~R.~Srinivasa
Rao, and C.~R.~Rao.
