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