MachineLearningNotebooks/how-to-use-azureml/azureml-sdk-for-r/vignettes

Azure Machine Learning vignettes

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

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 in the current working directory.

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-to-aci: 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).

Before you run these samples, make sure you have an Azure Machine Learning workspace. You can follow the configuration vignette to set up a workspace. (You do not need to do this if you are running these examples on an Azure Machine Learning compute instance).

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