azureml-sdk-for-r/vignettes

Azure ML vignettes

These vignettes are end-to-end tutorials for using Azure Machine Learning with the R SDK.

Before running a vignette in RStudio, set the working directory to the folder that contains the vignette file (.Rmd file) in RStudio using setwd(dirname) or Session -> Set Working Directory -> To Source File Location. Each vignette assumes that the data and scripts are relative to vignette file location.

The following vignettes are included:

1. installation: Install the Azure ML SDK for R.
2. configuration: Set up an Azure ML workspace.
3. train-and-deploy-first-model: Train a caret model and deploy as a web service to Azure Container Instances (ACI).
4. train-with-tensorflow: Train a deep learning TensorFlow model with Azure ML.
5. hyperparameter-tune-with-keras: Hyperparameter tune a Keras model using HyperDrive, Azure ML's hyperparameter tuning functionality.
6. deploy-to-aks: Production deploy a model as a web service to Azure Kubernetes Service (AKS).

If you are running these examples on an Azure Machine Learning compute instance, skip the installation and configuration vignettes (#1 and #2), as the compute instance has the Azure ML SDK pre-installed and your workspace details pre-configured.

For additional examples on using the R SDK, see the samples folder.

Azure ML guides

In addition to the end-to-end vignettes, we also provide more detailed documentation for the following:

• Deploying models: Where and how to deploy models on Azure ML.
• Troubleshooting: Known issues and troubleshooting for using R in Azure ML.