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 3.3 - http://docs.h2o.ai/sparkling-water/3.3/latest-stable/doc/pysparkling.html
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
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_3.0-3.42.0.1.post1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | bef44e60fb5ce99d8d79dc1a048295ea79357b3b7d4ffb28e277d436995d5f88 |
|
MD5 | c0e93ee214a08c681d15186a61bf256c |
|
BLAKE2b-256 | 08698f8cffb0825a8c596b7c1aaf05f29f18be51b0705737513d3f70459b65bd |