Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark
Project description
This package contains complete functionality for training and scoring Sparkling Water/H2O-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 3.2 - http://docs.h2o.ai/sparkling-water/3.2/latest-stable/doc/pysparkling.html
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_2.2-3.36.1.1-1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 97a812f4a838c1951f1b68e6ac0dd51128cc36cc5796adc9c04af78356e02c2a |
|
MD5 | 4f564aac3f9f7d1f58ef4ceca2658c1d |
|
BLAKE2b-256 | 6c6d0f4656cf19577c6383a3ea1da6ef42766aaf235f1e42613b48b5ae26839f |