In this video, learn why and how to track assets and code you’re creating in an end to end machine learning workflow.

Time Index:

• [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

For More Info:

• MLOps: Model management, deployment, and monitoring with Azure Machine Learning
• Data access in Azure Machine Learning
• Notebook tutorial showed in the video
• Git Integration