H2o
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An open-source, in-memory platform for distributed and scalable machine learning with support for a wide range of algorithms and big data technologies.
A minimal benchmark comparing scalability, speed, and accuracy of popular open-source machine learning libraries for binary classification.
Sparkling Water provides H2O functionality inside Spark cluster
A curated list of research, applications, tutorials, and software built using the H2O open-source machine learning platform.
A dashboard for real-time tracking and 72-hour forecasting of US electricity demand using open-source tools.
Provides parsnip model wrappers for H2O machine learning algorithms, enabling integration with the tidymodels ecosystem.
Automates AWS EMR cluster deployment and Spark job submission with integrated logging and PySparkling support for H2O.
Transpiles H2O POJO models to JavaScript for browser-based execution using JSweet and browserify.
Generates interactive R Markdown interfaces for h2o MOJO model files to explore predictions and model details.
Implementation of the Partitioning Around Medoids (PAM) clustering algorithm within the H2O-3 machine learning platform.
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