[tomfaulhaber]

Engineer on the SageMaker team here.

There are no restrictions on the types of algorithms that you can optimize using the HyperParameterOptimization service.

SageMaker is designed for machine learning which means it's optimized for algorithms that process a lot of data to develop a model where each run of the algorithm may generate an objective function value (or potentially many such as the value may change during training).

If this structure fits your problem, SageMaker could be useful to you even if your problem isn't strictly "machine learning."

[michaelbarton]

That's great. Thank you for following up so quickly. Could you point me to where I could read about this, or see an example?

I took a quick search on the documentation and I could see anything on a cursory pass:

http://docs.aws.amazon.com/search/doc-search.html?searchPath...

[tomfaulhaber]

Sorry, for the very delayed reply here.

The hyperparameter optimization feature is still in preview (though the rest of SageMaker is in general availability). We'll be putting up a page within the next week or so for you to request access.