There is lots still to say: enough to fill another book! This chapter will introduce quite a few topics, without going into too much detail, but pointing you toward where you can find out more.
This chapter starts with a look at where to get the latest documentation, and how to Use The Source, Luke! Then we look at how to upgrade H2O, and how to install it from source. Which leads on to how to set up clusters, which leads on to Spark and Sparkling Water. Finally, a look at other algorithms: naive bayes and ensembles.
H2O is well-documented, so http://docs.h2o.ai should be your first port of call. The latest user guide is at http://docs.h2o.ai/h2o/latest-stable/h2o-docs/index.html.
If you want to see if, say, any new parameters have been added to GBM, you could go to the REST API Reference, then find GBMParametersV3. Alternatively, regularly check Changes.md over on the GitHub site!
Random forest is called DRF in the REST endpoints, and hex.tree.drf in the Java source; everything else is fairly much named how you would expect.