[williamsmj]

I'd be interested in the creator's thoughts on this paper, "Random Search and Reproducibility for Neural Architecture Search", https://arxiv.org/abs/1902.07638, posted on the arxiv last week. Among other conclusions, they find:

"Our results show that random search with early-stopping is a competitive NAS baseline, e.g., it performs at least as well as ENAS, a leading NAS method, on both benchmarks"

ENAS, the specific algorithm that they find does no better than chance, is in this library. My understanding is that the results are pretty generic though, i.e. NAS is very far from a solved problem. (Hyperparameter tuning for "classical" models are another matter. That's commoditized and available as a service at this point, see tpot, DataRobot, etc., etc.)