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_3.2-3.38.0.1-1.tar.gz (161.7 MB view details)

Uploaded Source

File details

Details for the file h2o_pysparkling_3.2-3.38.0.1-1.tar.gz.

File metadata

  • Download URL: h2o_pysparkling_3.2-3.38.0.1-1.tar.gz
  • Upload date:
  • Size: 161.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/0.0.0 pkginfo/1.8.3 readme-renderer/27.0 requests/2.28.1 requests-toolbelt/0.9.1 urllib3/1.26.11 tqdm/4.64.0 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_3.2-3.38.0.1-1.tar.gz
Algorithm Hash digest
SHA256 2faef76dd7e2313c35aad1ece7aec069b69100bacf55bfa41df0a5b8a6c1f008
MD5 af05001068c79533e15731fa8d11a696
BLAKE2b-256 b384065c070a625cdd384c0edfbfca18527f84142658b13bbe0e6e5b92f62179

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