On the Modeler page, select the ‘From File’ tab. In the Choose asset type page, select Modeler Flow. To create an initial machine learning flow:įrom the Assets page, click Add to project. The change has no effect on how the service functions or is navigated. NOTE: You might notice that the “IBM Watson Studio” banner will in some cases be replaced with the name “IBM Cloud Pak for Data.” The banner used is dependent on the number and types of services that you have created on your IBM Cloud account. If you have finished setting up your environment, continue with the next step, creating a model flow.
You must complete these steps before continuing with the learning path.
To skip to Watson Studio Desktop, see SPSS Modeler flow using Watson Studio Desktop. The same steps to create an SPSS Modeler flow mentioned below for Watson Studio on IBM Cloud also apply to Watson Studio Desktop.
The SPSS Modeler flow feature is also available on IBM Watson Studio Desktop. It should take you approximately 60 minutes to complete this tutorial. To complete the tutorials in this learning path, you need an IBM Cloud account, which gives you access to IBM Cloud, IBM Watson Studio, and the IBM Watson Machine Learning Service. This tutorial introduces the SPSS Modeler components and explains how you can use them to build, test, evaluate, and deploy models.Īs with all the other tutorials in this learning path, we are using a customer churn data set that is available on Kaggle. IBM Watson SPSS Modeler flows in Watson Studio provide an interactive environment for quickly building machine learning pipelines that flow data from ingestion to transformation to model building and evaluation, without needing any code. This tutorial explains how to graphically build and evaluate machine learning models by using the SPSS Modeler flow feature in IBM® Watson™ Studio.
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