Building Machine Learning Applications with Sparkling Water: Writing applications which are processing and analyzing large amount of data is still hard. It often requires to design and run Machine Learning experiments in small scale and then consolidate them into a form of application and run them in large scale. There are several distributed machine learning platforms which are trying to mitigate this effort. In this talk we will focus on Sparkling Water which is combining benefits of two platforms – H2O and Spark. H2O is an open-source distributed math-engine providing tuned Machine Learning library, Spark is an execution platform which allows for processing large amount of data. The talk will demonstrate Sparkling Water features and shows its benefits for building rich and robust Machine Learning applications.