Provides overview, installation, set up, configuration, and customization information for Cloudera Data Science Workbench engines.
Provides an overview of engines and walks you through some of the ways you can customize engine environments to meet the requirements of your users and projects.
Models and Experiments
Provides information on how to build, deploy, and manage models on Cloudera Data Science Workbench.
Describes how to configure and manage engines in Cloudera Data Science Workbench.
Describes the availabile options for mounting a project's dependencies into its engine environment.
Provides a description of engine environment variables and how to use them to customize your experience with Workbench console.
Describes how to install and use additional libraries for specific project versions.
Describes how to create and install customized engine images.
Provides a list of packages included in the Python and R kernels of the base engine that ships with each release of Cloudera Data Science Workbench.