Building Machine Learning Models at Scale with Sparkling Water

Presented by

Elena Boiarskaia, Senior Solutions Engineer at

About this talk

H2O-3 is an open source, in-memory, distributed machine learning platform that is optimized to build machine learning models on big data and easily deploy them in an enterprise environment with a MOJO. Spark is a powerful distributed cluster-computing framework for running large-scale data processing workloads. Sparkling Water combines the best of both worlds, by seamlessly integrating the H2O-3 ML library to run on top of Spark for building fast and accurate predictive models on big data at scale. In this webinar, you will learn about: - Leveraging the power of H2O-3 and Spark to build scalable machine learning models - Embedding Sparkling Water models inside SparkML pipelines - End-to-end Sparkling Water use cases from data preparation to model deployment
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