Bill Gallmeister, VP of Engineering at H2O.ai, shows what's latest and greatest in H2O & Steam and shares the roadmap. - Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai - To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata

1. CONFIDENTIAL
Bill Gallmeister
October 26th, 2016
What’s Happening in H2O
and Steam?

2. H2O
Available Now:
• MOJO (bigger, faster POJOs)
• SSL for secure connections
• Partial Dependence Plots to help in Feature
Selection
• K-Means Improvements for more Precise clustering
• Generally better solutions
• Automatic K calculation
• Automatic centroid initialization
• Reproducible results
• Parquet and JDBC Support
Coming Up:
• Deep Water
• AutoML
• GLRM improvements (MOJO, Performance)

3. H2O GBM Performance
With the usual caveats, of course: dataset matters, as do configuration parameters

4. Steam
First Released 9/16: AGPL and Commercial Licenses
available
Available Now:
• YARN Launch
• Cluster Connect
• MOJO Support
• Deep Water Support
Coming Up:
• AutoML
• Sparkling Water Support
• Enterprise Security Integrations

5. Deep Water
Tensorflow &
Mxnet &
Caffe &
H2O Deep Learning
http://deepwater.h2o.ai/classy-demo/

6. Sparkling Water
Available Now:
• Spark 2.0 Support
• Sparkling
• Support of Spark DataSets
• Spark Query Optimization
• we can now benefit from Spark optimizer
and fetch only a subset of H2OFrame
Coming Up:
• Improved Robustness via JVM separation