{"id":5387,"date":"2021-04-20T08:20:40","date_gmt":"2021-04-20T06:20:40","guid":{"rendered":"https:\/\/joapen.com\/blog\/?p=5387"},"modified":"2021-05-04T14:07:49","modified_gmt":"2021-05-04T12:07:49","slug":"what-is-machine-learning-operations","status":"publish","type":"post","link":"http:\/\/joapen.com\/blog\/2021\/04\/20\/what-is-machine-learning-operations\/","title":{"rendered":"What is Machine Learning Operations"},"content":{"rendered":"\n<p class=\"has-normal-font-size\">If you are reading this and you are not me, you should navigate to this link: <a rel=\"noreferrer noopener\" href=\"https:\/\/ml-ops.org\/\" target=\"_blank\">https:\/\/ml-ops.org\/<\/a><\/p>\n\n\n\n<p>There are so many basis and nice charts that explain What is Machine Learning Operations (or ml-ops). I&#8217;m doing a summary for me \ud83d\ude42<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Definition of MLOps<\/h2>\n\n\n\n<p>The term Machine Learning Operations is defined as&nbsp;<em>\u201cthe extension of the DevOps methodology to include Machine Learning and Data Science assets as first-class citizens within the DevOps ecology<\/em>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Overview of the End-to-End Machine Learning Workflow<\/h2>\n\n\n\n<p>The main phases are:<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Data Engineering<\/strong>: data acquisition &amp; data preparation,<\/li><li><strong>ML Model Engineering<\/strong>: ML model training &amp; serving, and<\/li><li><strong>Code Engineering<\/strong>&nbsp;:integrating ML model into the final product.<\/li><\/ul>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/ml-ops.org\/img\/ml-engineering.jpg\" alt=\"Machine Learning Engineering\"\/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Iterative-Incremental Process in MLOps<\/h2>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/ml-ops.org\/img\/mlops-loop-en.jpg\" alt=\"Agile ML Workflow\"\/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Automation<\/h2>\n\n\n\n<p>The level of automation of the Data, ML Model, and Code pipelines determines the maturity of the ML process.<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>Manual process<\/li><li>ML pipeline automation<\/li><li>CI\/CD pipeline automation<\/li><\/ol>\n\n\n\n<p>The following picture shows the automated ML pipeline with CI\/CD routines:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/ml-ops.org\/img\/mlops-phasen.jpg\" alt=\"Automated ML Pipeline\"\/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Data Version Control<\/h2>\n\n\n\n<p>If you have the lifecycle of your code operating under DevOps and you are using Git to manage all this, how do you manage the versions of data when adding machine learning projects? One possible answer is: Data Version Control.<\/p>\n\n\n\n<p><a rel=\"noreferrer noopener\" href=\"https:\/\/dvc.org\/\" target=\"_blank\">DVC.org<\/a> is an Open-source Version Control System for Machine Learning Projects. They have some nice videos where you can see how it works and how they implement so many of the best practices from ml-ops.<\/p>\n\n\n\n<p>For instance, this introduction video: <a rel=\"noreferrer noopener\" href=\"https:\/\/www.youtube.com\/watch?v=UbL7VUpv1Bs&amp;t=2s\" target=\"_blank\">https:\/\/www.youtube.com\/watch?v=UbL7VUpv1Bs&amp;t=2s<\/a><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>If you are reading this and you are not me, you should navigate to this link: https:\/\/ml-ops.org\/ There are so many basis and nice charts that explain What is Machine Learning Operations (or ml-ops). I&#8217;m doing a summary for me \ud83d\ude42 Definition of MLOps The term Machine Learning Operations is defined as&nbsp;\u201cthe extension of the &#8230; <a title=\"What is Machine Learning Operations\" class=\"read-more\" href=\"http:\/\/joapen.com\/blog\/2021\/04\/20\/what-is-machine-learning-operations\/\" aria-label=\"Read more about What is Machine Learning Operations\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":5402,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[151],"tags":[215],"class_list":["post-5387","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning","tag-mlops"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What is Machine Learning Operations -<\/title>\n<meta name=\"description\" content=\"If you are reading this and you are not me, you should navigate to this link: https:\/\/ml-ops.org\/ There are so many basis and nice charts that explain - 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