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
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_3.0-3.34.0.3-1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 386546703e024d78a52fd5b124d417f5b2722f732d736f6bd40d3162f3540772 |
|
MD5 | c706866bc598235c7e1efa35d7e16d08 |
|
BLAKE2b-256 | 267d1e65277abd45be3a9654b2805ccb97eb1c0f5454000c3c19c22b1c3f2860 |