Efficient Machine Learning in H2O with R and Python, Part 1 - DATAVERSITY

One of the major benefits of working with R and Python for analytics is that there're always new and freely-available treats from their vibrant open source ecosystems. And now more and more, data scientists are able to reap the benefits of working with data in R, Python and other platforms simultaneously, as vendors introduce performant products with APIs to both R and Python -- in addition to perhaps Java, Scala and Spark. An example with which I'm currently quite smitten is H2O. H2O brands as "AI for Business" that "makes it possible for anyone to easily apply math and predictive analytics to solve today's most challenging business problems." What sets H2O apart is its comprehensive, open source, cross-platform, machine learning infrastructure architected from the ground up for scalability and speed.