H2O is an open-source, distributed in-memory machine learning platform with linear scalability. H2O supports the most widely used statistical & machine learning algorithms, including gradient boosted machines, generalized linear models, and deep learning, amongst others. Build with mobile applications; it aids in programming languages like Java, R and Python. Its use cases are data analysis, customer intelligence, and risk analysis, amongst others. H2O works on existing big data infrastructure, on bare metal or existing Hadoop, Spark or Kubernetes clusters. It can ingest data directly from HDFS, Spark, S3, Azure Data Lake or any other data source into it’s in-memory distributed key-value store.


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