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https://github.com/rstudio/cloudml

R interface to Google Cloud Machine Learning Engine
https://github.com/rstudio/cloudml

cloudml gpc gpu keras r rstats tensorflow

Last synced: about 2 months ago
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R interface to Google Cloud Machine Learning Engine

Host: GitHub
URL: https://github.com/rstudio/cloudml
Owner: rstudio
Created: 2017-02-17T19:29:06.000Z (almost 8 years ago)
Default Branch: main
Last Pushed: 2021-11-22T19:12:30.000Z (about 3 years ago)
Last Synced: 2024-08-03T22:04:35.962Z (5 months ago)
Topics: cloudml, gpc, gpu, keras, r, rstats, tensorflow
Language: R
Homepage: https://tensorflow.rstudio.com/tools/cloudml/
Size: 3.34 MB
Stars: 65
Watchers: 13
Forks: 24
Open Issues: 26
Metadata Files:
- Readme: README.md

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README

        

## R interface to Google CloudML

[![Build Status](https://travis-ci.org/rstudio/cloudml.svg?branch=master)](https://travis-ci.org/rstudio/cloudml) [![AppVeyor Build

Status](https://ci.appveyor.com/api/projects/status/github/rstudio/cloudml?branch=master&svg=true)](https://ci.appveyor.com/project/JavierLuraschi/cloudml) [![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/cloudml)](https://cran.r-project.org/package=cloudml)

The **cloudml** package provides an R interface to [Google Cloud Machine Learning Engine](https://cloud.google.com/ml-engine/), a managed service that enables:

* Scalable training of models built with the [keras](https://keras.rstudio.com/), [tfestimators](https://tensorflow.rstudio.com/tfestimators), and [tensorflow](https://tensorflow.rstudio.com/) R packages.

* On-demand access to training on GPUs, including the new [Tesla P100 GPUs](http://www.nvidia.com/object/tesla-p100.html) from NVIDIA®.

* Hyperparameter tuning to optimize key attributes of model architectures in order to maximize predictive accuracy.

* Deployment of trained models to the Google global prediction platform that can support thousands of users and TBs of data.

CloudML is a managed service where you pay only for the hardware resources that you use. Prices vary depending on configuration (e.g. CPU vs. GPU vs. multiple GPUs). See  for additional details.

For documentation on using the R interface to CloudML see the package website at