Machine Learning
      Projects in Cloudera Machine Learning
      Date published: 2020-07-16
      Date modified:
      https://docs.cloudera.com/
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                                                Machine Learning | Contents | iii
      Contents
         Projects in Cloudera Machine Learning................................................................4
            Creating a Project with Legacy Engine Variants.................................................................................................4
            Adding Project Collaborators...............................................................................................................................5
            Modifying Project Settings...................................................................................................................................6
            Managing Project Files.........................................................................................................................................7
            Custom Template Projects....................................................................................................................................8
            Deleting a Project................................................................................................................................................. 8
         Native Workbench Console and Editor................................................................. 9
            Launch a Session.................................................................................................................................................. 9
            Run Code............................................................................................................................................................ 10
            Access the Terminal........................................................................................................................................... 11
            Stop a Session.....................................................................................................................................................11
         Third-Party Editors................................................................................................12
            Modes of Configuring Third-Party Editors........................................................................................................12
            Configure a Browser IDE as an Editor..............................................................................................................14
               Test a Browser IDE in a Session Before Installation............................................................................14
               Configure a Browser IDE at the Project Level......................................................................................15
               Configure a Browser IDE at the Engine Level......................................................................................15
            Configure a Local IDE using an SSH Gateway................................................................................................ 18
            Configure PyCharm as a Local IDE..................................................................................................................18
               Add Cloudera Machine Learning as an Interpreter for PyCharm..........................................................19
               Configure PyCharm to use Cloudera Machine Learning as the Remote Console................................. 19
               (Optional) Configure the Sync Between Cloudera Machine Learning and PyCharm........................... 20
         Git for Collaboration..............................................................................................20
            Linking an Existing Project to a Git Remote.................................................................................................... 21
         Web Applications Embedded in Sessions.............................................................21
            Example: A Shiny Application.......................................................................................................................... 22
      Machine Learning                                                                                                       Projects in Cloudera Machine Learning
                 Projects in Cloudera Machine Learning
                        Projects form the heart of Cloudera Machine Learning. They hold all the code, configuration, and libraries needed to
                        reproducibly run analyses. Each project is independent, ensuring users can work freely without interfering with one
                        another or breaking existing workloads.
                        Access the Projects page by clicking Projects in the navigation panel. The Projects page gives you a quick summary
                        of project information.
                        •   Active Workloads - If there are active workloads running, this section describes the number of Sessions,
                            Experiments, Models, Jobs, and Applications that are running.
                        •   Resource Usage Details - A collapsible section that displays resource usage.
                            •   Active Workloads - If there are active workloads running, this section describes the number of Sessions,
                                Experiments, Models, Jobs, and Applications that are running.
                            •   User Resources and Workspace Resources
                                •   Click on the User Resources tab to see the CPU and memory resource usage for the user. The maximum
                                    usage of the vCPU and GB is calculated based on whether or not you have a quota. If you have a quota, the
                                    maximum usage will be based on your quota. If you don't have a quota, the maximum usage will be what is
                                    available on the cluster. If you have a GPU, you'll also see the GPU usage.
                                •   Click on the Workspace Resources tab to see usage overall.
                        •   Search Projects - Enter a term for keyword search across Project names.
                        •   Scope - An additional filter only viewable by Administrators.
                            •   Selecting My Projects displays only the Projects that you have created or are a Collaborator of.
                            •   Selecting All Projects displays all Projects on the ML Workspace.
                        •   Creator - An additional filter to only display Projects created by a specified user.
                        •   Projects View Selector - A setting that enables you to display Projects in a summary card-based view or a detailed
                            table-based view.
                        The following topics describe how to create and manage projects in Cloudera Machine Learning.
                 Creating a Project with Legacy Engine Variants
                        Projects create an independent working environment to hold your code, configuration, and libraries for your analysis.
                        This topic describes how to create a project with Legacy Engine variants in Cloudera Machine Learning.
                        Procedure
                        1. Go to Cloudera Machine Learning and on the left sidebar, click Projects.
                                                                                       4