13 frameworks for mastering machine learningOn August 17, 2017 by Zander
H2O, now in its third major revision, provides access to machine learning algorithms by way of common development environments (Python, Java, Scala, R), big data systems (Hadoop, Spark), and data sources (HDFS, S3, SQL, NoSQL). H2O is meant to be used as an end-to-end solution for gathering data, building models, and serving predictions. For instance, models can be exported as Java code, allowing predictions to be served on many platforms and in many environments.
H2O can work as a native Python library, or by way of a Jupyter Notebook, or by way of the R language in R Studio. The platform also includes an open source, web-based environment called Flow, exclusive to H2O, which allows interacting with the dataset during the training process, not just before or after.