Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark
Project description
This package contains complete functionality for training and scoring Sparkling Water/H20-3 MOJO models. It’s also possible to use this package for scoring with Driverless AI MOJO models.
PySparkling Documentation is hosted at our documentation page:
For Spark 3.1 - http://docs.h2o.ai/sparkling-water/3.1/latest-stable/doc/pysparkling.html
For Spark 3.0 - http://docs.h2o.ai/sparkling-water/3.0/latest-stable/doc/pysparkling.html
For Spark 2.4 - http://docs.h2o.ai/sparkling-water/2.4/latest-stable/doc/pysparkling.html
For Spark 2.3 - http://docs.h2o.ai/sparkling-water/2.3/latest-stable/doc/pysparkling.html
For Spark 2.2 - http://docs.h2o.ai/sparkling-water/2.2/latest-stable/doc/pysparkling.html
For Spark 2.1 - http://docs.h2o.ai/sparkling-water/2.1/latest-stable/doc/pysparkling.html
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Hashes for h2o_pysparkling_2.2-3.32.1.3-1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | e851c1561ad6279c5bfc6690e8c3b5a13facdd404c2aceb41562fdce2261aa7a |
|
MD5 | eff3c49adc1a9c13be6cd14d3d7f078c |
|
BLAKE2b-256 | f9bc65273e37bba9a8a5421aa4d22c5abb1e8592b3e7f9f96329172e47f39aca |