Amazon has announced the availability of RStudio for SageMaker. The move is designed to make it easier to use RStudio with SageMaker’s machine learning and deep learning capabilities, and to incorporate RStudio into the data science infrastructure on SageMaker.

RStudio is an integrated development environment (IDE) for R includes a code console, syntax-highlighting editor, and tools for plotting, history, debugging and workspace management.

Amazon SageMaker is a fully-managed platform that can be used to build, train, and deploy machine learning models at any scale. It includes hosted Jupyter notebooks for exploring and visualizing your training data stored in Amazon S3. You can connect directly to data in S3, or use AWS Glue to move data from Amazon RDS, Amazon DynamoDB, and Amazon Redshift into S3 for analysis in your notebook.

The inclusion means data scientists can launch RStudio Workbench with a simple click from within SageMaker. The inclusion also supports startinh a new session with a fully-configured environment, and choosing an instance type with the desired compute and memory for the job at hand, from a wide array of ML instances available.

Within the SageMaker/RStudio environment, users can get access to their organization’s data stored on AWS. They also have access to all of SageMaker’s deep learning capabilities, accessed via Python libraries using the reticulate package. This preconfigured environment includes all the necessary SageMaker libraries to get started.

The RStudio support complements Amazon SageMaker Studio Notebooks, which provide access to Python coding in a Jupyter Notebook environment, so that it's possible to switch between RStudio and SageMaker Studio Notebooks. All users' work, including code, datasets, repositories, and other artifacts are synchronized between the two environments through the default Amazon Elastic File System (Amazon EFS) storage.

RStudio for Amazon SageMaker is available now.

More Information

RStudio Website

Amazon SageMaker

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