Dear H2O Community,
 #H2OWorld  is on Monday and we can’t wait to see you there! We’ll also be live streaming the event  starting at 9:25am PST. Explore the agenda here .
 Today we’re excited to share that new versions of H2O-3 and Sparkling Water are available.
 We invite you to download them here:
 http://www.h2o.ai/download/ 
H2O-3.16 
 – MOJOs are now supported for Stacked Ensembles.
 – Easily specify the meta-learner algorithm type that Stacked Ensemble should use. This can be AUTO, GLM, GBM, DRF or Deep Learning .
 – GBM, DRF now support custom evaluation metrics.
 – The AutoML leaderboard now uses cross-validation  metrics (new default).
 – Multiclass stacking is now supported in AutoML . Removed the check that caused AutoML to skip stacking for multiclass.
 – The Aggregator Function is now exposed in the Python/R client.
 – Support for Python 3.6.
 Detailed changes and bug fixes can be found here:
 https://github.com/h2oai/h2o-3/blob/master/Changes.md 
 Sparkling Water 2.0, 2.1, 2.2 
 – Support for H2O Models into Spark python pipelines.
 – Improved handling of sparse vectors  in internal cluster.
 – Improved stability of external cluster deployment mode.
 – Includes latest H2O-3.16.0.2.
 Detailed changes and bug fixes can be explored here:
 2.2 – https://github.com/h2oai/sparkling-water/blob/rel-2.2/doc/CHANGELOG.rst 
 2.1 – https://github.com/h2oai/sparkling-water/blob/rel-2.1/doc/CHANGELOG.rst 
 2.0 – https://github.com/h2oai/sparkling-water/blob/rel-2.0/doc/CHANGELOG.rst 
 Hope to see you on Monday!
 The H2O.ai Team