Before we get started, we will download some assets and complete some setup for our workshop. This section is broken up into the following steps:
Various parts of this workshop will require the attendee to upload files or run scripts that we've stored in the repository. To download the repository and its assets, you have two options. Option 1, if you have the git
command line interface on your laptop, you can clone the repository directly. Option 2, if you don't have git you can access the GitHub repository page to download the zip file.
[Option 1] If you have the git CLI, run the following commands from a terminal or command prompt:
git clone https://github.com/IBM/credit-risk-workshop-cpd.gitcd credit-risk-workshop-cpd
[Option 2] To download the repository as a zip file, go to the GitHub repo for this workshop and download the archived version of the workshop and extract it on your laptop.
Note: If its not automatically done for you, make sure you extract or unzip the zip file after its downloaded.
At this point of the workshop we will be using Cloud Pak for Data for the remaining steps.
Launch a browser and navigate to your Cloud Pak for Data deployment.
NOTE: Your instructor will provide a URL and credentials to log into Cloud Pak for Data!
In Cloud Pak for Data, we use the concept of a project to collect / organize the resources used to achieve a particular goal (resources to build a solution to a problem). Your project resources can include data, collaborators, and analytic assets like notebooks and models, etc.
Go the (☰) navigation menu and click on the Projects link.
Click on the New project button on the top right.
Select the Analytics project
radio button and click the Next button.
We are going to create a project from an existing file (which contains the assets we will use throughout this workshop), as opposed to creating an empty project. Select the Create a project from a sample or file option.
Click on the browse link and in the file browser popup, navigate to where you cloned or downloaded this repository in the previous section. From within that root directory, navigate to the projects/
sub-directory and choose the CreditRiskProject.zip
file. Then click the open button.
Give the project a name and click the Create
button.
From the project creation succesfully created pop up window, click on the View new project button.
Cloud Pak for Data uses the concept of Deployment Spaces
to configure and manage the deployment of a set of related deployable assets. These assets can be data files, machine learning models, etc.
Go the (☰) navigation menu and click Analyze
-> Analytics deployments
.
Click on the New deployment space
button.
We will create an empty deployment space, so click on the Create an empty space
option.
Give your deployment space a unique name, optional description, then click the Create
button.
Next, we will add a collaborator to the new deployment space. Collaborators allow others to view/edit/manage the assets being deployed. In this workshop, we want the models we deploy to be visible and monitored in the OpenScale model monitoring lab.
Click on the Access control
tab and then click on Add collaborators
on the right.
Enter "admin" as a Collaborator input field and select the Admin
user from the drop down list. Then click on the Add to list
button.
NOTE: We are adding the user that configured the machine learning instance for OpenScale monitoring. In this case, the user is the admin user.
Click the Add
button to finish adding the collaborator. You should be brought back to the deployment space page and see your user ID along with the Admin
user as collaborators for this space.
We've completed creating the project and deployment space that we will be using for the rest of this workshop.