How do you propose to handle the scalability required for H2o model creation ?
On Tue, Oct 20, 2015 at 9:58 AM Siyuan Hua <[email protected]> wrote: > In ML model training, we discovered a pattern that apex can be used to > process raw data to feature data, then H2O takes the feature data into it's > model train engine to train the model. > > But there is a gap in between 2 pipelines, I have a proposal that we could > create some operator which feed the processed data directly into H2O or > maybe start a container for H2O and throw data into it. In that way, we > could build a continuous online model train pipeline. > > I've created a jira here https://malhar.atlassian.net/browse/MLHR-1875 > > Feel free to throw any thoughts > > Best, > Siyuan >
