{"id":866,"date":"2022-05-09T10:01:56","date_gmt":"2022-05-09T18:01:56","guid":{"rendered":"https:\/\/live-cometml.pantheonsite.io\/?p=866"},"modified":"2025-04-24T17:17:21","modified_gmt":"2025-04-24T17:17:21","slug":"introducing-comet-artifacts-lineage","status":"publish","type":"post","link":"https:\/\/www.comet.com\/site\/blog\/introducing-comet-artifacts-lineage\/","title":{"rendered":"Introducing Comet Artifacts Lineage"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Our latest product update eases tracking, reproducibility, and collaboration in ML experiment management<\/h2>\n\n\n\n<p>When you are building and training ML models, tracking, reproducibility, and collaboration can be challenging. And when you\u2019re doing deep learning experiment management, you can multiply that challenge.<\/p>\n\n\n\n<p>It\u2019s pain being experienced by a growing number of data scientists who are building ML: In a <a href=\"https:\/\/go.comet.ml\/report-machine-learning-practitioners-survey.html\" target=\"_blank\" rel=\"noreferrer noopener\">survey of more than 500 machine learning practitioners<\/a>, respondents cited challenges related to people, process, and tools that make it difficult to track model training runs and results, collaborate with colleagues, and iterate fast during the complex process of developing machine learning. This friction can cause delays in ML development that slow down or halt model deployment to production.<\/p>\n\n\n\n<p>Comet\u2019s latest product update aims to reduce that friction so you can get to the good part: Building better ML models faster.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Tracking <strong>Dataset Lineage<\/strong><\/h3>\n\n\n\n<p>As your team and your machine learning operations scale, it becomes more challenging to track and version datasets and to link dataset versions to the models they were used to create. You may want to analyze more granular aspects of the data, such as comparing different subsets of data, or perhaps explore how your data from a year ago is different from your data today, and how the data differs by model.<\/p>\n\n\n\n<p>Comet Artifacts Lineage provides an interactive way for you and your team to explore and compare datasets so you can better understand and visualize datasets you are using for machine learning. It also allows you to collaborate and report on your ML projects for easier reproducibility and, ultimately, more confidence in the performance of your models in production.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Where to Find Comet Artifacts Lineage<\/strong><\/h3>\n\n\n\n<p>Artifacts Lineage is available within the different versions of your Artifacts. To view the lineage of a dataset, select <em>Artifacts<\/em>, choose a dataset, and select <em>Lineage<\/em>. You will be able to view your Artifact assets, metadata, and lineage. Lineage makes it easier to reproduce models by allowing you to visualize, in an interactive way, how your model was created, how your data was used, and everything in between. Explore the entire experiment graph to find the right dataset and the right model.<\/p>\n\n\n\n<p>In your free Comet account, you can access a demo project and <a href=\"https:\/\/www.comet.com\/team-comet-ml\/artifacts\/DOTA_sample_100\" target=\"_blank\" rel=\"noreferrer noopener\">see Artifacts Lineage in action<\/a>.<\/p>\n\n\n\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our latest product update eases tracking, reproducibility, and collaboration in ML experiment management When you are building and training ML models, tracking, reproducibility, and collaboration can be challenging. And when you\u2019re doing deep learning experiment management, you can multiply that challenge. It\u2019s pain being experienced by a growing number of data scientists who are building [&hellip;]<\/p>\n","protected":false},"author":112,"featured_media":867,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"customer_name":"","customer_description":"","customer_industry":"","customer_technologies":"","customer_logo":"","footnotes":""},"categories":[8,9],"tags":[14,15,16],"coauthors":[131],"class_list":["post-866","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-comet-community-hub","category-product","tag-comet-ml","tag-deep-learning-experiment-management","tag-ml-experiment-management"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Introducing Comet Artifacts Lineage | Comet<\/title>\n<meta name=\"description\" content=\"Introducing Comet Artifacts Lineage: Our latest product update eases tracking, reproducibility, and collaboration in ML experiment management.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.comet.com\/site\/blog\/introducing-comet-artifacts-lineage\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Introducing Comet Artifacts Lineage\" \/>\n<meta property=\"og:description\" content=\"Introducing Comet Artifacts Lineage: Our latest product update eases tracking, reproducibility, and collaboration in ML experiment management.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.comet.com\/site\/blog\/introducing-comet-artifacts-lineage\/\" \/>\n<meta property=\"og:site_name\" content=\"Comet\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/cometdotml\" \/>\n<meta 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