In this project you will work through an end-to-end workflow broken into various sections to:
Read in data from a live source
Prepare your data in an IDE of your choice, with an option to leverage distributed computing clusters
Train several models in various frameworks
Compare model performance across different frameworks and select best performing model
Deploy model to a containerized endpoint and web-app frontend for consumption
Leverage collaboration and documentation capabilities throughout to make all work reproducible and sharable!
Guide your mouse to the sidebar and click the Search page. Afterwards, type the word Training in the cell provided and hit Enter to discover any projects tagged with Training. (The blue sidebar shrinks to show only the icon of the pages; unshrink it by guiding your mouse over the icon pages.)
Select the project called WineQuality.
In the top right corner, choose the icon to Fork the project. Name the project WineQuality.
Look at the readme to learn more about the project.
NoteIf you see No README present , click Jobs in the sidebar. Then click the blue Run button, enter “/repos/Domino-Launchpad-Quickstart/scripts/launchpad-init.sh” as the File Name, and hit Start. You should see the files appear if you go back to Overview in the sidebar and refresh the page in 30-60 seconds.
In your new project go to the Access and Sharing tab and change your project visibility to Public. This allows anyone with access to your Domino URL to see the files and executions in your project.
NoteOn LaunchPad, they must first have logged in with the NVIDIA-provided credentials.
Optional: If a colleague of yours has an account in this Domino, you can add them as a collaborator in your project.
Change their permissions to Results Consumer. This permission level does not allow them to start executions or change files in your project, but will allow them to see files and published artifacts.
Click back into the Overview area of your project. Then navigate to the Manage tab.
Click on Add Goals.
For the goal title, type in Explore Data and click Save. Once the goal is saved click the drop down on the right to mark the goal status as Data Acquisition and Exploration.
Optional: If you’ve already added a collaborator to Domino, add a comment to the goal and tag them by typing ‘@’ followed by their username. Click on the paper airplane to submit the comment.
We will now add a data connection to the project so we can query data. As a code-first platform, Domino allows you to connect to data with any Python/CLI/etc. tools you already use, but there are also UI methods that make it easier to share and manage your data sources.
To use one of these, navigate to Data in the sidebar of your project and click on Add a Data Source (you may need to click on the Data Sources tab first).
Select the WineQuality S3 bucket connection and click Add to project. This example connection was predefined by an admin, but it is possible for all users to create these.
The Data Source should look like the image below.
This concludes all sections in Step #01: Prepare Project and Data!
