Skip to main content

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.

Join the chat at https://gitter.im/h2oai/sparkling-water License Powered by H2O.ai

PySparkling Documentation is hosted at our documentation page:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

h2o_pysparkling_3.3-0.0.0.1-1.tar.gz (2.2 kB view details)

Uploaded Source

File details

Details for the file h2o_pysparkling_3.3-0.0.0.1-1.tar.gz.

File metadata

  • Download URL: h2o_pysparkling_3.3-0.0.0.1-1.tar.gz
  • Upload date:
  • Size: 2.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.7.9

File hashes

Hashes for h2o_pysparkling_3.3-0.0.0.1-1.tar.gz
Algorithm Hash digest
SHA256 6d60e9ce82c5f3024d4dc81473b48cd004446dd435c983616feab3a9e3a0bc04
MD5 8ca19cef6c14ebf2650242a91e59e607
BLAKE2b-256 1a25349dccd308a933e3682e9684a81db45ad3d9780bd55e22011d1acdfc05bb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page