{"id":8528,"date":"2023-06-16T03:23:04","date_gmt":"2023-06-16T03:23:04","guid":{"rendered":"http:\/\/edenai.co.za\/develop\/model-registries-explained\/"},"modified":"2023-07-20T07:32:06","modified_gmt":"2023-07-20T07:32:06","slug":"model-registries-explained","status":"publish","type":"post","link":"https:\/\/edenai.co.za\/develop\/model-registries-explained\/","title":{"rendered":"Model Registries Explained"},"content":{"rendered":"\nWhen it comes to Machine Learning (ML) development there are many tools created to help assist developers. Model registries are in ML development. Although they seem similar to version control they have different use\u00a0cases.<\/p>\n<h3>What is a Model\u00a0Registry<\/h3>\n<p><a href=\"https:\/\/towardsdatascience.com\/ml-model-registry-the-interface-that-binds-model-experiments-and-model-deployment-f6df00f0b695\">Yunna Wei<\/a> defines a model registry as a centralised place to store all your ML artefacts along with their metadata from early-stage experiments to production-ready models. This allows ML teams to collaborate on models by providing model organisation, discovery, versioning, the ability to trace the origin of the model and the ability to manage production statuses of your\u00a0models.<\/p>\n<h3>Importance of Model\u00a0registry<\/h3>\n<p>Dominick Rocco <a href=\"https:\/\/www.phdata.io\/blog\/what-is-a-model-registry\/\">states<\/a> that without a model registry, data scientists and machine learning engineers are more likely to cut corners or make costly mistakes such\u00a0as:<\/p>\n<p>Mislabeled model artefacts and difficulties tracking files from training\u00a0jobs.Lost or deleted\u00a0dataMissing source code or unknown versions as even good models sometimes have\u00a0errors.Undocumented model performance which makes it hard to compare different versions<\/p>\n<p>On top of avoiding the negatives of not having one there are many positives to having a model registry. <a href=\"https:\/\/neptune.ai\/blog\/ml-model-registry\">Stephen Oladele<\/a> further elaborates on this by listing the positives of having a model registry:<\/p>\n<p>Having a model registry enables faster deployment of your models by bridging the gap between experiment and production activities resulting in a faster production model rollout. It also stores trained models to be quickly retrieved.Having a model registry simplifies model lifecycle management by simplifying the management of your model lifecycleHaving a model registry enables production model governance by centralising models and organising their relevant\u00a0detailsHaving a model registry can help improve the security of your model by managing specific versions of the packages that you can scan and remove security vulnerabilities that may pose a threat to the\u00a0system.<\/p>\n<p>In summary, version control software is used for managing changes to the codebase and other files in a machine learning project, while a model registry is used to manage and deploy machine learning models. We at Eden AI are more happy to set up model registries for production workload. Contact us @<a href=\"mailto:helloworld@edenai.co.za\">helloworld@edenai.co.za<\/a> and we will help\u00a0you.<\/p>\n<p>\u200bStories by Eden AI on Medium\u00a0\u00a0<\/p>\n<p>\u200b<a href=\"https:\/\/medium.com\/@socialedenai\/model-registries-explained-8b28a4f230c8?source=rss-ecb4628d2f9------2\" target=\"_blank\" class=\"feedzy-rss-link-icon\" rel=\"noopener\">Read More<\/a>\u00a0\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When it comes to Machine Learning (ML) development there are many tools created to help assist [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":34756,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-fullwidth.php","format":"standard","meta":{"_crdt_document":"","footnotes":""},"categories":[70],"tags":[],"class_list":["post-8528","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-medium-posts"],"_links":{"self":[{"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/posts\/8528","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/comments?post=8528"}],"version-history":[{"count":2,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/posts\/8528\/revisions"}],"predecessor-version":[{"id":9212,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/posts\/8528\/revisions\/9212"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/media\/34756"}],"wp:attachment":[{"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/media?parent=8528"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/categories?post=8528"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/edenai.co.za\/develop\/wp-json\/wp\/v2\/tags?post=8528"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}