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{"title":"Release note 03.09.20","slug":"release-note-030920","body":"## DATA CRUNCHER MULTIPLE ENVIRONMENT SETUPS\n\nWhen selecting your Data Cruncher environment, you are now able to chose between different environment setups for your JupyterLab or RStudio analysis. Each environment setup is a set of preinstalled libraries that is available every time an analysis is started and is intended for a specific purpose.\n\nFor this first release, we are enabling support for *machine learning* use cases using CPU or GPU instances. [Learn more](doc:about-libraries-in-a-data-cruncher-analysis).","_id":"5e6667bbd4250e002d973bf6","changelog":[],"createdAt":"2020-03-09T15:58:51.677Z","user":{"name":"Marko Marinkovic","username":"","_id":"5767bc73bb15f40e00a28777"},"initVersion":{"version":"1.0","_id":"5773dcfc255e820e00e1cd50"},"project":"5773dcfc255e820e00e1cd4d","__v":0}

Release note 03.09.20

By Marko Marinkovic · · v1.0

## DATA CRUNCHER MULTIPLE ENVIRONMENT SETUPS When selecting your Data Cruncher environment, you are now able to chose between different environment setups for your JupyterLab or RStudio analysis. Each environment setup is a set of preinstalled libraries that is available every time an analysis is started and is intended for a specific purpose. For this first release, we are enabling support for *machine learning* use cases using CPU or GPU instances. [Learn more](doc:about-libraries-in-a-data-cruncher-analysis).