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).<p>I know that folks are having some success with Gaussian process optimisation for hyper parameter tuning (eg <a href="https:&#x2F;&#x2F;github.com&#x2F;Yelp&#x2F;MOE" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Yelp&#x2F;MOE</a>), 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&#x27;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.