1 Introduction

These are short notes of getting up and running quickly with H2O in an R environment. The notes cover installation of H2O from R and a simple use case aimed at showcasing the use of H2O from R.

1.1 Wondering what H2O is?

H2O is an open source platform that aims to allow easy scaling of machine learning algorithms and predictive analytics to big data and provides easy productionalization of those models in an enterprise environment. All this brought to you in the comfort of your preferred data analysis language. For a detailed explanation of what H2O is and what it aims to do, refer to this part of the documentation.

1.2 Other resources

  • For a broad, probably exhaustive coverage of functionalities offered by H2O, one can have a look at H2O’s documentation. The folks at H2O really did a magnificent job
  • The book Practical Machine Learning with H2O by Darren Cook is a good hands-on guide of using H2O
  • H2O’s Amy Wang gives a hands on introductory training in this video titled H2O - Hands on with R, Python and Flow

Feel free to email me with questions,comments or suggestions.