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Get started with Python
Step 0: Orient yourself to DominoStep 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get started with R
Step 0: Orient yourself to Domino (R Tutorial)Step 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get Started with MATLAB
Step 1: Orient yourself to DominoStep 2: Create a Domino ProjectStep 3: Configure Your Domino ProjectStep 4: Start a MATLAB WorkspaceStep 5: Fetch and Save Your DataStep 6: Develop Your ModelStep 7: Clean Up Your Workspace
Step 8: Deploy Your Model
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Get started with R
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Step 2: Configure your project

Step 2: Configure your project

Every project has its own settings. The following options are important to consider when configuring a new project:

  • Hardware Tier

  • Environment

  • Collaborators

Step 2.1: Select your hardware tier

A Hardware Tier represents the compute resources that will be available for your run. You can specify memory, CPU cores, and GPUs with hardware tiers.

The hardware tier dropdown menu lists your available options. The selected hardware tier will be used by default for all subsequent executions of code in the project. It can also be changed at any point in the future.

  1. In the Project menu, click Settings.

  2. Click the Hardware tier menu to select the compute resource from which to execute your code. Choose the smallest or default hardware tier for this tutorial. Your options might look different from the following image.

    Hardware tier dropdown

    This list of available hardware tiers is customizable by your Domino administrators. If you want additional resources, contact your Domino administrator.

Step 2.2: Configure your environment

An Environment is a Domino abstraction on top of a Docker image that provides additional flexibility and versioning. You can configure the software, packages, libraries, and drivers that you need in your environment.

Domino comes with a default environment called the Domino Analytics Distribution (DAD), which includes Python, R, Jupyter, RStudio, and key data science related packages and libraries.

  1. Click the Compute Environment menu to select the default project Environment.

  2. Choose the Python 3 version of the Domino Analytics Distribution.

Compute environment dropdown

Your compute environment dropdown will likely have different options. If you’re interested in learning how to add more packages and customize or create your own Environment, see the help article on Domino Environments.

Compute environment dropdown

Step 2.3: Configure the project permissions

As the owner of the project, you can set different access levels for collaborators and colleagues. Feel free to invite a colleague to be a Contributor to your project.

  1. Click the Access & Sharing tab.

    collaborator panel

  2. (Optional) Enter the email or the username of the user that you would like to invite.

  3. (Optional) Enter a welcome message to be sent to your collaborator.

The Contributor role allows the invited user to read, write, and execute code in this project.

Visit the Collaborators and permissions support article for more information on the permissions for each collaborator role

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