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_2.2-3.34.0.4-1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 02dcc5f6c49759b56fd35d3b1b0c78109f8c152978742ab8404e562f795e6038 |
|
MD5 | 4b87f850ba9834d3f304f7c7f8adb642 |
|
BLAKE2b-256 | fcde751f70035d97fd8441658fa657e18132191f1404ca1b446cf88895f67b0a |