This is like FB's FBLearner, which I've used a little bit. This is a platform, so this is not at at the SKL/Tensorflow/Caffe level, this is something which say

This is like FB's FBLearner, which I've used a little bit. This is a platform, so this is not at at the SKL/Tensorflow/Caffe level, this is something which says: put your data in our data warehouse in this format, tell me what model you want to run on it, go have a coffee, and by the time you're back I'll magically run your model on a big cluster quickly; if you want I can also try out different hyperparams/models, and I'll give you standard plots/metrics to evaluate the thing. You can also use 1000s of existing feature vectors/metrics that other people have put in the DWH. You can also clone an existing model and tweak that. If you're happy with the model, you can deploy, either on my API by querying and I'll tell you the prediction, or I can publish the model in binary form to a datastore and you can just import it in your iOS code in 3 lines. You can also schedule nightly re-trains, I'll notify you if something big changes in the accuracy metrics, etc. The point is, this sort of ML platform allows engineers at big companies to leverage existing data/metrics/f.vectors, models, infra, etc. and allows them to move 10-100x faster than startups/hobbyists. When I say 10-100x, I actually mean it, I'm also running ML models at home, and the amount of time I waste on this glue stuff is huge (starting from data prep to f---ing around with tensor ranks). I'm sure there are already startups working on platforms like this for everybody, we'll just have to wait for one of those to become good.