Jupyter Notebooks with R in Azure Machine Learning Studio

March 30, 2016

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

by Andrie de Vries

Earlier today Microsoft announced that Jupyter Notebooks are now available with the R Kernel as a service in Azure Machine Learning (ML) Studio.

I wrote about Jupyter Notebooks in September 2015 (Using R with Jupyter Notebooks), where I noted some of the great benefits of using notebooks:

  • Jupyter is an easy to use and convenient way of mixing code and text in the same document.
  • Unlike other reporting systems like RMarkdown and LaTex, Jupyter notebooks are interactive – you can run the code snippets directly in the document
  • This makes it easy to share and publish code samples as well as reports.

This new announcement is that Jupyter Notebooks with R are now a feature of the Azure Machine Learning Studio. This means:

  1. You can create and edit R notebooks directly in the Azure ML cloud, without having to create virtual machines.
  2. Using the AzureML R package, you can interact between R notebooks and your Azure ML environment. Specifically, you can:
    • Download and upload datasets
    • Download intermediate datasets from Azure ML experiments
    • Publish and consume web services
  3. You can easily publish your notebook in the Cortana Intelligence Gallery, either privately or publicly.


See notebooks in action

This video has a gentle introduction on how to use Jupyter Notebooks:


See some sample notebooks

We have created some examples that demonstrates the possibilities:

 You can find these notebooks, and others, in the Cortana Intelligence Gallery:


Published notebooks in the Cortana Intelligence Gallery

How to try the notebooks in Azure ML

You can try the notebook service, as well as all of the Azure ML Studio, using a free guest account.

  1. Go to http://studio.azureml.net/
  2. Click "Sign up".
    • This will give you the option to use a guest account, a free account or a standard workspace
    • Capture-signup
  3. For completely anonymous access, choose "Guest Workspace"
    • However, note that in a guest workspace you won't be able to save your work.
    • In a "Free Workspace" you can save your work and publish notebooks.
  4. Take the option to do the quick tour, if you wish, otherwise skip this step
  5. Click the Notebook tab on the left
    • Capture-notebook
  6. You now have a range of sample notebooks to choose from. You can select either a new R notebook, or one of the sample notebooks.
    • Notice that some of the notebooks are Python and some are R.
    • You can tell the difference by looking for the small "R" icon in the top right hand corner of each tile
  7. Click on "Blank R Notebook", or open one of the other R sample notebooks
    • Capture-R
    • Code away!
    • To run code in a cell, click "Shift + Enter"


The Jupyter project is an open source project with many contributors. Thank you to the Jupyter team, as well as the IRKernel team who did the integration work between Jupyter and R.

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Get more information

The announcement blog post contains more detail about the features of notebooks and the integration with Azure ML Studio.

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

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