From 3abbd8cadc5928ce9c8fcd93e8da516e88b5f3df Mon Sep 17 00:00:00 2001 From: Muhammad Rizwan Munawar Date: Sun, 19 Jan 2025 18:47:55 +0500 Subject: [PATCH] Add https://youtu.be/zCupPHqSLTI to docs (#18743) --- docs/en/guides/model-monitoring-and-maintenance.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/docs/en/guides/model-monitoring-and-maintenance.md b/docs/en/guides/model-monitoring-and-maintenance.md index 2933de45..79fa52ea 100644 --- a/docs/en/guides/model-monitoring-and-maintenance.md +++ b/docs/en/guides/model-monitoring-and-maintenance.md @@ -10,6 +10,17 @@ keywords: Computer Vision Models, AI Model Monitoring, Data Drift Detection, Ano If you are here, we can assume you've completed many [steps in your computer vision project](./steps-of-a-cv-project.md): from [gathering requirements](./defining-project-goals.md), [annotating data](./data-collection-and-annotation.md), and [training the model](./model-training-tips.md) to finally [deploying](./model-deployment-practices.md) it. Your application is now running in production, but your project doesn't end here. The most important part of a computer vision project is making sure your model continues to fulfill your [project's objectives](./defining-project-goals.md) over time, and that's where monitoring, maintaining, and documenting your computer vision model enters the picture. +

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+ Watch: How to Maintain Computer Vision Models after Deployment | Data Drift Detection +

+ In this guide, we'll take a closer look at how you can maintain your computer vision models after deployment. We'll explore how model monitoring can help you catch problems early on, how to keep your model accurate and up-to-date, and why documentation is important for troubleshooting. ## Model Monitoring is Key