Yes, but does it work? I cannot tell from reading the introductory materials whether it will actually search efficiently over large space (where it is computationally expensive to evaluate the fitness of any individual point).

I know that folks are having some success with Gaussian process optimisation for hyper parameter tuning (eg https://github.com/Yelp/MOE), but I would be sceptical about the application of genetic programming to this area, particularly as broadly defined a search space as TPOT seems to set up (genetic programming either doesn't make assumptions about the objective function being optimised which can be used to search more efficiently, like Gaussian optimisation does - or uses implicit assumptions that may be unsuitable, depending on how you want to think about it); has anyone seen benchmarks against other search methods? The workflow does look great though - integrating it into scikit looks really clever.