Graphically build and evaluate machine learning models by using SPSS Modeler flow in Watson Studio on Cloud Pak for Data

Graphically-build-and-evaluate-machine-learning-models-by-using-SPSS-Modeler-flow-in-Watson-Studio-on-Cloud-Pak-for-Data

In this hands-on tutorial you will graphically build and evaluate machine learning models by using the SPSS Modeler flow feature in Watson Studio.

If you don’t have one already, please Sign up for an IBM Cloud account.

This tutorial consists of 6 parts, you can start with part I or any other part, however, the necessary environment is set up in part I.
Part I – data visualization, preparation, and transformation
Part II – build and evaluate machine learning models by using AutoAI
Part III – graphically build and evaluate machine learning models by using SPSS Modeler flow
Part IV – set up and run Jupyter Notebooks to develop a machine learning model
Part V – deploy a local Python app to test your model
Part VI – monitor your model with OpenScale

SPSS Modeler flow is a ‘Drag and Drop’ tool to build a machine learning model in your Watson Studio project. You can either use the file provided on GitHub to set up your modeler flow or create a new one.

To access the complete tutorial go to this GitHub Repository.

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