The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

cloudml: Interface to the Google Cloud Machine Learning Platform

Interface to the Google Cloud Machine Learning Platform <https://cloud.google.com/ml-engine>, which provides cloud tools for training machine learning models.

Version: 0.6.1
Depends: R (≥ 3.3.0), tfruns (≥ 1.3)
Imports: config, jsonlite, packrat, processx, rprojroot, rstudioapi, tools, utils, withr, yaml
Suggests: tensorflow (≥ 1.4.2), keras (≥ 2.1.2), knitr, testthat
Published: 2019-09-03
DOI: 10.32614/CRAN.package.cloudml
Author: Daniel Falbel [aut, cre], Javier Luraschi [aut], JJ Allaire [aut], Kevin Ushey [aut], RStudio [cph]
Maintainer: Daniel Falbel <daniel at rstudio.com>
License: Apache License 2.0
NeedsCompilation: no
SystemRequirements: Python (>= 2.7.0)
Materials: NEWS
In views: ModelDeployment
CRAN checks: cloudml results

Documentation:

Reference manual: cloudml.pdf
Vignettes: Deploying Models
Getting Started
Google Cloud Storage
Training with CloudML
Hyperparameter Tuning

Downloads:

Package source: cloudml_0.6.1.tar.gz
Windows binaries: r-devel: cloudml_0.6.1.zip, r-release: cloudml_0.6.1.zip, r-oldrel: cloudml_0.6.1.zip
macOS binaries: r-release (arm64): cloudml_0.6.1.tgz, r-oldrel (arm64): cloudml_0.6.1.tgz, r-release (x86_64): cloudml_0.6.1.tgz, r-oldrel (x86_64): cloudml_0.6.1.tgz
Old sources: cloudml archive

Reverse dependencies:

Reverse suggests: tfdeploy

Linking:

Please use the canonical form https://CRAN.R-project.org/package=cloudml to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.