{"id":8339,"date":"2026-08-10T09:54:49","date_gmt":"2026-08-10T09:54:49","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/oreilly-distributed-machine-learning-patterns-video-edition-2024-1\/"},"modified":"2026-08-10T09:54:49","modified_gmt":"2026-08-10T09:54:49","slug":"oreilly-distributed-machine-learning-patterns-video-edition-2024-1","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/oreilly-distributed-machine-learning-patterns-video-edition-2024-1\/","title":{"rendered":"Oreilly \u2013 Distributed Machine Learning Patterns, Video Edition 2024-1"},"content":{"rendered":"<div class=\"w-post-elm post_content\">\n<h2><span style=\"vertical-align: inherit\">Description<\/span><\/h2>\n<p><span style=\"vertical-align: inherit\">Distributed Machine Learning Patterns Video Edition. This course explores practical patterns for scaling machine learning from your personal laptop to a distributed cluster. In this course, participants will learn techniques and expert tips for tackling the challenges of scaling machine learning systems.<\/span><\/p>\n<p data-sourcepos=\"9:1-9:565\"><span style=\"vertical-align: inherit\">Distributed machine learning systems allow developers to manage very large datasets across multiple clusters, leverage automation tools, and take advantage of hardware accelerations. Distributed Machine Learning Patterns reveals best practice techniques and insider tips for tackling the scalability challenges of machine learning systems. In this book, Yuan Tang, project lead for Argo and Kubeflow, shares patterns, examples, and insights gained from his experience migrating an ML model from a single machine to a distributed cluster.<\/span><\/p>\n<h3><span style=\"vertical-align: inherit\">What you will learn<\/span><\/h3>\n<ul>\n<li data-sourcepos=\"3:1-7:69\"><span style=\"vertical-align: inherit\">You will apply distributed systems patterns to build scalable and reliable machine learning projects. You will build ML pipelines with data ingestion, distributed training, model serving, and more.<\/span><\/li>\n<li data-sourcepos=\"3:1-7:69\"><span style=\"vertical-align: inherit\">You will automate ML tasks with Kubernetes, TensorFlow, Kubeflow, and Argo Workflows.<\/span><\/li>\n<li data-sourcepos=\"3:1-7:69\"><span style=\"vertical-align: inherit\">You will make the right choices between different patterns and approaches.<\/span><\/li>\n<li data-sourcepos=\"3:1-7:69\"><span style=\"vertical-align: inherit\">You will manage and monitor machine learning workloads at scale.<\/span><\/li>\n<\/ul>\n<h3 data-sourcepos=\"9:1-9:26\"><span style=\"vertical-align: inherit\">This course is suitable for people who:<\/span><\/h3>\n<ul>\n<li data-sourcepos=\"11:1-11:101\"><span style=\"vertical-align: inherit\">There are data analysts and engineers who are familiar with the basics of machine learning, Bash, Python, and Docker.<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Distributed Machine Learning Patterns Video Edition Course Details<\/span><\/h3>\n<ul>\n<li><span style=\"vertical-align: inherit\">Publisher: <\/span><a href=\"https:\/\/href.li\/?https:\/\/www.oreilly.com\/library\/view\/distributed-machine-learning\/9781617299025VE\/\/\" target=\"_blank\" rel=\"noopener\"><span style=\"vertical-align: inherit\">Oreilly<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Instructor: <\/span><a href=\"https:\/\/downloadlynet.ir\/tag\/yuan-tang\/\"><span style=\"vertical-align: inherit\">Yuan Tang<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Training level: Beginner to advanced<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Training duration: 6 hours and 21 minutes<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course topics<\/span><\/h3>\n<ul>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Part 1. Basic concepts and background<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 1. Introduction to distributed machine learning systems<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 1. Distributed systems<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 1. Distributed machine learning systems<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 1. What we will learn in this book<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 1. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Part 2. Patterns of distributed machine learning systems<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. Data ingestion patterns<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. The Fashion-MNIST dataset<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. Batching pattern<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. Sharding pattern: Splitting extremely large datasets among multiple machines<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. Caching pattern<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 2. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 3. Distributed training patterns<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 3. Parameter server pattern: Tagging entities in 8 million YouTube videos<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 3. Collective communication pattern<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 3. Elasticity and fault-tolerance pattern<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 3. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 3. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 4. Model serving patterns<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 4. Replicated services pattern: Handling the growing number of serving requests<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 4. Sharded services pattern<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 4. The event-driven processing pattern<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 4. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 4. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 5. Workflow patterns<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 5. Fan-in and fan-out patterns: Composing complex machine learning workflows<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 5. Synchronous and asynchronous patterns: Accelerating workflows with concurrency<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 5. Step memoization pattern: Skipping redundant workloads via memoized steps<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 5. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 5. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 6. Operation patterns<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 6. Scheduling patterns: Assigning resources effectively in a shared cluster<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 6. Metadata pattern: Handle failures appropriately to minimize the negative effect on users<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 6. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 6. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Part 3. Building a distributed machine learning workflow<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. Project overview and system architecture<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. Data ingestion<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. Model training<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. Model serving<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. End-to-end workflow<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 7. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 8. Overview of relevant technologies<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 8. Kubernetes: The distributed container orchestration system<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 8. Kubeflow: Machine learning workloads on Kubernetes<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 8. Argo Workflows: Container-native workflow engine<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 8. Answers to exercises<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 8. Summary<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 9. A complete implementation<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 9. Model training<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 9. Model serving<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 9. The end-to-end workflow<\/span><\/li>\n<li class=\"toc-level-1 t-toc-level-1\" dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Chapter 9. Summary<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course images<\/span><\/h3>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-960095 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2025\/01\/Distributed-Machine-Learning-Patterns-Video-Edition2.png\" alt=\"Distributed Machine Learning Patterns Video Edition \" width=\"1121\" height=\"358\"><\/h2>\n<h3><span style=\"vertical-align: inherit\">Sample course video<\/span><\/h3>\n<div style=\"width: 640px;\" class=\"wp-video\"><span class=\"mejs-offscreen\">Video Player<\/span><\/p>\n<div id=\"mep_0\" class=\"mejs-container mejs-container-keyboard-inactive wp-video-shortcode mejs-video\" tabindex=\"0\" role=\"application\" aria-label=\"Video Player\" style=\"width: 640px; height: 360px; min-width: 217px;\">\n<div class=\"mejs-inner\">\n<div class=\"mejs-mediaelement\"><mediaelementwrapper id=\"video-153020-1\"><video class=\"wp-video-shortcode\" id=\"video-153020-1_html5\" width=\"640\" height=\"360\" preload=\"metadata\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Distributed_Machine_Learning_Patterns_Video_Edition_Downloadly.ir.mp4?_=1\" style=\"width: 640px; height: 360px;\"><source type=\"video\/mp4\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Distributed_Machine_Learning_Patterns_Video_Edition_Downloadly.ir.mp4?_=1\"><a href=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Distributed_Machine_Learning_Patterns_Video_Edition_Downloadly.ir.mp4?nocache=1786112049183\">https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Distributed_Machine_Learning_Patterns_Video_Edition_Downloadly.ir.mp4<\/a><\/video><\/mediaelementwrapper><\/div>\n<div class=\"mejs-layers\">\n<div class=\"mejs-poster mejs-layer\" style=\"display: none; width: 100%; height: 100%;\"><\/div>\n<div class=\"mejs-overlay mejs-layer\" style=\"display: none; width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-loading\"><span class=\"mejs-overlay-loading-bg-img\"><\/span><\/div>\n<\/div>\n<div class=\"mejs-overlay mejs-layer\" style=\"display: none; width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-error\"><\/div>\n<\/div>\n<div class=\"mejs-overlay mejs-layer mejs-overlay-play\" style=\"width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-button\" role=\"button\" tabindex=\"0\" aria-label=\"Play\" aria-pressed=\"false\"><\/div>\n<\/div>\n<\/div>\n<div class=\"mejs-controls\">\n<div class=\"mejs-button mejs-playpause-button mejs-play\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Play\" aria-label=\"Play\" tabindex=\"0\"><\/button><\/div>\n<div class=\"mejs-time mejs-currenttime-container\" role=\"timer\" aria-live=\"off\"><span class=\"mejs-currenttime\">00:00<\/span><\/div>\n<div class=\"mejs-time-rail\"><span class=\"mejs-time-total mejs-time-slider\" role=\"slider\" tabindex=\"0\" aria-label=\"Time Slider\" aria-valuemin=\"0\" aria-valuemax=\"0\" aria-valuenow=\"0\" aria-valuetext=\"00:00\"><span class=\"mejs-time-buffering\" style=\"display: none;\"><\/span><span class=\"mejs-time-loaded\"><\/span><span class=\"mejs-time-current\"><\/span><span class=\"mejs-time-hovered no-hover\"><\/span><span class=\"mejs-time-handle\"><span class=\"mejs-time-handle-content\"><\/span><\/span><span class=\"mejs-time-float\"><span class=\"mejs-time-float-current\">00:00<\/span><span class=\"mejs-time-float-corner\"><\/span><\/span><\/span><\/div>\n<div class=\"mejs-time mejs-duration-container\"><span class=\"mejs-duration\">00:00<\/span><\/div>\n<div class=\"mejs-button mejs-volume-button mejs-mute\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Mute\" aria-label=\"Mute\" tabindex=\"0\"><\/button><a href=\"javascript:void(0);\" class=\"mejs-volume-slider\" aria-label=\"Volume Slider\" aria-valuemin=\"0\" aria-valuemax=\"100\" role=\"slider\" aria-orientation=\"vertical\"><span class=\"mejs-offscreen\">Use Up\/Down Arrow keys to increase or decrease volume.<\/span><\/p>\n<div class=\"mejs-volume-total\">\n<div class=\"mejs-volume-current\" style=\"bottom: 0px; height: 100%;\"><\/div>\n<div class=\"mejs-volume-handle\" style=\"bottom: 100%; margin-bottom: -3px;\"><\/div>\n<\/div>\n<p><\/a><\/div>\n<div class=\"mejs-button mejs-fullscreen-button\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Fullscreen\" aria-label=\"Fullscreen\" tabindex=\"0\"><\/button><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div>\n<h3><span style=\"vertical-align: inherit\">Installation Guide<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">After Extract, view with your favorite player.<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Subtitles: None<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Quality: 720p<\/span><\/p>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">Download link<\/span><\/h3>\n<p><a href=\"https:\/\/dl1.downloadly.ir\/Files\/Elearning\/Oreilly_Distributed_Machine_Learning_Patterns,_Video_Edition_2024-1_Downloadly.ir.rar?nocache=1786112048\"><span style=\"vertical-align: inherit\">Download file \u2013 868 MB<\/span><\/a><\/p>\n<p><span style=\"vertical-align: inherit\">File(s) password: www.downloadly.ir<\/span><\/p>\n<h3><span style=\"vertical-align: inherit\">File size<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">868 MB<\/span><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Description Distributed Machine Learning Patterns Video Edition. This course explores practical patterns for scaling machine learning from your personal laptop <\/p>\n","protected":false},"author":1,"template":"","dgi_category":[10458],"dgi_tag":[73994,73995,73996,73997,73998,73999],"class_list":["post-8339","digital_item","type-digital_item","status-publish","has-post-thumbnail","hentry","dgi_category-video-tutorials","dgi_tag-course-distributed-machine-learning-patterns-video-edition","dgi_tag-download-course-distributed-machine-learning-patterns-video-edition","dgi_tag-download-distributed-machine-learning-patterns-video-edition","dgi_tag-free-distributed-machine-learning-patterns-video-edition","dgi_tag-free-download-distributed-machine-learning-patterns-video-edition","dgi_tag-yuan-tang"],"_links":{"self":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item\/8339","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item"}],"about":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/types\/digital_item"}],"author":[{"embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":0,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item\/8339\/revisions"}],"wp:attachment":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/media?parent=8339"}],"wp:term":[{"taxonomy":"dgi_category","embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/dgi_category?post=8339"},{"taxonomy":"dgi_tag","embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/dgi_tag?post=8339"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}