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_2.4-3.36.0.1-1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 19e5f9766ed77adeb29d7a903f776970a44055e48b98de56beb7f3adc51a02da |
|
MD5 | 17333b90d96ddf332bb1466ea0a04f89 |
|
BLAKE2b-256 | 4b1b769fd4b229fac172b555b6182922bc170b0092cc7c657e3911f9269bf299 |