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. Deeplearning4j – Iris Classification Example
  4. Solid Modelling for 3D Printing for the JVM in Jupyterlab
  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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