{"id":121,"date":"2021-07-16T15:36:04","date_gmt":"2021-07-16T15:36:04","guid":{"rendered":"https:\/\/felixaugenstein.com\/blog\/?p=121"},"modified":"2021-07-16T15:36:04","modified_gmt":"2021-07-16T15:36:04","slug":"graphically-build-and-evaluate-machine-learning-models-by-using-spss-modeler-flow-in-watson-studio-on-cloud-pak-for-data","status":"publish","type":"post","link":"https:\/\/felixaugenstein.com\/blog\/graphically-build-and-evaluate-machine-learning-models-by-using-spss-modeler-flow-in-watson-studio-on-cloud-pak-for-data\/","title":{"rendered":"Graphically build and evaluate machine learning models by using SPSS Modeler flow in Watson Studio on Cloud Pak for Data"},"content":{"rendered":"\n

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

If you don\u2019t have one already, please Sign up for an IBM Cloud account<\/a>.<\/p>\n\n\n\n

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 \u2013 data visualization, preparation, and transformation<\/a>
Part II \u2013 build and evaluate machine learning models by using AutoAI<\/a>
Part III \u2013 graphically build and evaluate machine learning models by using SPSS Modeler flow<\/a>
Part IV \u2013 set up and run Jupyter Notebooks to develop a machine learning model<\/a>
Part V \u2013 deploy a local Python app to test your model<\/a>
Part VI \u2013 monitor your model with OpenScale<\/a><\/p>\n\n\n\n

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.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

To access the complete tutorial go to this GitHub Repository<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

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\u2019t have one already, please Sign up for an IBM Cloud account. This tutorial consists of 6 parts, you can start with part I or […]<\/p>\n","protected":false},"author":1,"featured_media":122,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21,4,25],"tags":[],"class_list":["post-121","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cloud-pak-for-data","category-ibm-watson","category-spss-modeler"],"_links":{"self":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/121","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/comments?post=121"}],"version-history":[{"count":1,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/121\/revisions"}],"predecessor-version":[{"id":124,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/121\/revisions\/124"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/media\/122"}],"wp:attachment":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/media?parent=121"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/categories?post=121"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/tags?post=121"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}