Describes how to create and manage projects in Cloudera Data Science Workbench.
Provides information on how to create, customize, manage, and delete a project.
Provides information on how to use the Workbench console to start and stop sessions, execute code, and access the terminal to run engines from the web console.
Describes how to use the visualization system to create plots.
Describes how to use GPUs to accelerate highly parallelized, computationally-intensive workloads.
Describes how to use embedded web applications for frameworks such as Spark 2, TensorFlow, and Shiny within sessions.
Describes how to access user interfaces for applications such as Cloudera Manager and Hue directly from the Cloudera Data Science Workbench UI.
Describes how to run distributed machine learning workloads on the CDH/HDP cluster with frameworks such as TensorFlowOnSpark, H2O, and XBoost.
Describes how to launch multiple engine instances from a single interactive session.
Describes how to git to collaborate on projects.