joeyrichar

This is exactly what we're enabling with our ML Platform (currently in private beta). Such a system needs to be built on top of fast & scalable ML technology with smart & efficient tuning/optimization.

Would love to hear about your use cases & get you on the beta.

-Joey Richards, Chief Scientist @ wise.io

Thanks for the comments.

(1) We chose to do our original benchmarks against R, Weka and sklearn because these are the tools that the vast majority of people currently use. You'd be amazed how many companies use Weka! That said, we do benchmark favorably against the other competition. We will be publishing a series of blog posts with these benchmarks. Stay tuned!

(2) Our titles in fact do mark a clear delineation between our respective roles and responsibilities, and this is well understood within the company. Perhaps the titles are a bit grandiose, but we have a very big vision for this company.

(1) The speed-up is achieved on a single core (multithreaded). The tiny memory footprint enables us to do embedded learning (e.g., on an ARM chip). We also have a distributed version of WiseRF in development (stay tuned!).

(2) Soon, we'll be publishing a series of blog posts to benchmark WiseRF against competing implementations. Look for that next week.

Thanks for your interest!

As textminer says, RFs are really nice in that there are few parameters to tune, and the results typically are not that sensitive to the choice of those parameters (contrasted to, say, SVMs, where you can get killed in performance with a poor choice of tuning parameters).

With the MLaaS platform, all of the model optimization is taken care of under the hood (we also allow users to do their own parameter selection / tuning if desired). Our super fast implementation, WiseRF (10-100x faster than RF in sklearn or R) enables us to efficiently explore the hyperparameter space.

Thanks again for your questions and comments.

Joey Richards, Chief Scientist, wise.io

Ozten, we completely agree which is why we also provide an on premise version of our Machine Intelligence Engine. Our mission is to democratize ML and allow companies to easily deploy it in production.

Thanks for the interest and feedback!

Joey Richards, Chief Scientist, wise.io