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_3.1-3.32.1.6-1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | e022894acda322ad0aeaedc1ba7629172315f302f40289da1f2ce1aadcf5c4df |
|
MD5 | 1f6568131b487c4f1b5e2300ab6283fc |
|
BLAKE2b-256 | 0b2b5d6df82623463a86b2f86ee385dda44f99234f893a358fb81b89c9149824 |