MLOps feature dive: Manage your assets, artifacts and code

From the creator

In this video, you’ll learn why and how to track assets and code you’re creating in an end to end machine learning workflow. Jump To: [01:20] How to track assets and artifacts [04:20] Demo - How to keep track of code [05:58] Why it's important to manage datasets + Demo More Information: MLOps: Model management, deployment, and monitoring with Azure Machine Learning - https://aka.ms/ModelManagement Data access in Azure Machine Learning - https://aka.ms/DataAccessinAML Notebook tutorial showed in the video - https://aka.ms/NotebookTutorial Git Integration - https://aka.ms/GitIntegration The AI Show's Favorite links: Don't miss new episodes, subscribe to the AI Show: https://aka.ms/aishowsubscribe Create a Free account (Azure): https://aka.ms/aishow-seth-azurefree Deep Learning vs. Machine Learning: https://aka.ms/AIShow/DLvML Get Started with Machine Learning: https://aka.ms/AIShow/StartML Follow: https://twitter.com/sethjuarez Follow: https://twitter.com/ch9 Follow: https://twitter.com/Azure Follow: https://twitter.com/msdev #AIShow

Published 2020-03-24 · Watch on YouTube ↗
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