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_3.2-3.40.0.2-1.tar.gz (162.2 MB view details)

Uploaded Source

File details

Details for the file h2o_pysparkling_3.2-3.40.0.2-1.tar.gz.

File metadata

  • Download URL: h2o_pysparkling_3.2-3.40.0.2-1.tar.gz
  • Upload date:
  • Size: 162.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/0.0.0 pkginfo/1.9.6 readme-renderer/27.0 requests/2.28.1 requests-toolbelt/0.10.1 urllib3/1.26.14 tqdm/4.64.1 importlib-metadata/4.8.1 keyring/23.2.1 rfc3986/2.0.0 colorama/0.4.5 CPython/3.6.15

File hashes

Hashes for h2o_pysparkling_3.2-3.40.0.2-1.tar.gz
Algorithm Hash digest
SHA256 28499d67c5bfce7c41cf3419791c722b93534c999b65faecb4879440ddf3a0df
MD5 1d2b724c58a29ab28fc28e0b3f475aa3
BLAKE2b-256 6cab81a97491c6ee30bb8b289781edb971f079905d633972e4afaacc33bce84b

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