azuremlsdk: Interface to the 'Azure Machine Learning' 'SDK'

Interface to the 'Azure Machine Learning' Software Development Kit ('SDK'). Data scientists can use the 'SDK' to train, deploy, automate, and manage machine learning models on the 'Azure Machine Learning' service. To learn more about 'Azure Machine Learning' visit the website: <>.

Version: 1.10.0
Depends: R (≥ 3.5.0)
Imports: ggplot2, reticulate (≥ 1.12), plyr (≥ 1.8), DT, rstudioapi (≥ 0.7), htmltools, servr, shiny, shinycssloaders
Suggests: rmarkdown, knitr, testthat, dplyr, jsonlite, foreach, iterators, utils
Published: 2020-09-22
Author: Diondra Peck [cre, aut], Minna Xiao [aut], AzureML R SDK Team [ctb], Microsoft [cph, fnd], Google Inc. [cph] (Examples and Tutorials), The TensorFlow Authors [cph] (Examples and Tutorials), RStudio Inc. [cph] (Examples and Tutorials)
Maintainer: Diondra Peck <Diondra.Peck at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: azuremlsdk results


Reference manual: azuremlsdk.pdf
Vignettes: Set up an Azure ML workspace
Deploy a web service to Azure Kubernetes Service
Deploying models
A Deeper Dive into Experiments
Hyperparameter tune a Keras model
Install the Azure ML SDK for R
Train and deploy your first model with Azure ML
Train a TensorFlow model
Known issues and troubleshooting
Package source: azuremlsdk_1.10.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: azuremlsdk_1.10.0.tgz, r-oldrel: azuremlsdk_1.10.0.tgz
Old sources: azuremlsdk archive


Please use the canonical form to link to this page.