H2O Deployment in Scala, Groovy, Kotlin….

Published by pschatzmann on

The H2O MOJO and POJO models can be deployed to production w/o the need of any access to a running H2O or Spark Instance. I am providing some examples using Jupyter with different BeakerX kernels.

see also:

  1. H2O Sparkling Water – Distributed Random Forrest
  2. Deeplearning4j – Recurrent Neural Networks (RNN)
  3. Solid Modelling for 3D Printing for the JVM in Jupyterlab
  4. Deeplearning4j – Iris Classification Example
  5. Random Forrest Classifier in Spark ML
  6. Using Shogun in the JVM
  7. NFS in Docker-Compose
  8. An OpenSCAD Kernel for Jupyter
  9. Parametrized Cork Pals in Scad4J
  10. Modules in Scad4J
Categories: Machine Learning

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