{"id":125,"date":"2021-07-16T15:45:26","date_gmt":"2021-07-16T15:45:26","guid":{"rendered":"https:\/\/felixaugenstein.com\/blog\/?p=125"},"modified":"2021-07-16T15:45:26","modified_gmt":"2021-07-16T15:45:26","slug":"set-up-and-run-jupyter-notebooks-to-develop-a-machine-learning-model-in-watson-studio-on-cloud-pak-for-data","status":"publish","type":"post","link":"https:\/\/felixaugenstein.com\/blog\/set-up-and-run-jupyter-notebooks-to-develop-a-machine-learning-model-in-watson-studio-on-cloud-pak-for-data\/","title":{"rendered":"Set up and run Jupyter Notebooks to develop a machine learning model in Watson Studio on Cloud Pak for Data"},"content":{"rendered":"\n<p>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<p>If you don\u2019t have one already, please Sign up for an <a href=\"https:\/\/cloud.ibm.com\/registration\" target=\"_blank\" rel=\"noreferrer noopener\">IBM Cloud account<\/a>.<\/p>\n\n\n\n<p>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.<br><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial\" target=\"_blank\">Part I \u2013 data visualization, preparation, and transformation<\/a><br><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-ii\" target=\"_blank\">Part II \u2013 build and evaluate machine learning models by using AutoAI<\/a><br><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-iii\" target=\"_blank\">Part III \u2013 graphically build and evaluate machine learning models by using SPSS Modeler flow<\/a><br><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-iv\" target=\"_blank\">Part IV \u2013 set up and run Jupyter Notebooks to develop a machine learning model<\/a><br><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-v\" target=\"_blank\">Part V \u2013 deploy a local Python app to test your model<\/a><br><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-vi\" target=\"_blank\">Part VI \u2013 monitor your model with OpenScale<\/a><\/p>\n\n\n\n<p>To learn more about Jupyter and Jupyter Notebooks <a href=\"https:\/\/jupyter.org\/\" data-type=\"URL\" data-id=\"https:\/\/jupyter.org\/\" target=\"_blank\" rel=\"noreferrer noopener\">click here<\/a>.<\/p>\n\n\n\n<p>Definitions from <a href=\"https:\/\/jupyter.org\/\" data-type=\"URL\" data-id=\"https:\/\/jupyter.org\/\" target=\"_blank\" rel=\"noreferrer noopener\">jupyter.org<\/a> for Project Jupyter and Jupyter Notebooks are:<\/p>\n\n\n\n<p>&#8220;Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages.&#8221;<\/p>\n\n\n\n<p>&#8220;The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.&#8221;<\/p>\n\n\n\n<p>In your Watson Studio project you can also add new Notebooks and start developing your machine learning models.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"506\" src=\"https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-1024x506.png\" alt=\"\" class=\"wp-image-127\" srcset=\"https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-1024x506.png 1024w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-300x148.png 300w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-768x379.png 768w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-1536x759.png 1536w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-2048x1012.png 2048w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-830x410.png 830w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-230x114.png 230w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-350x173.png 350w, https:\/\/felixaugenstein.com\/blog\/wp-content\/uploads\/2021\/07\/jupyter-notebook-480x237.png 480w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>To access the complete tutorial go to this <a href=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-iv\" data-type=\"URL\" data-id=\"https:\/\/github.com\/FelixAugenstein\/cloud-pak-for-data-tutorial-part-iv\" target=\"_blank\" rel=\"noreferrer noopener\">GitHub Repository<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>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 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":126,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21,4,26,20],"tags":[],"class_list":["post-125","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cloud-pak-for-data","category-ibm-watson","category-jupyter-notebook","category-watson-studio"],"_links":{"self":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/125","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=125"}],"version-history":[{"count":1,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/125\/revisions"}],"predecessor-version":[{"id":128,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/125\/revisions\/128"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/media\/126"}],"wp:attachment":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/media?parent=125"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/categories?post=125"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/tags?post=125"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}