In this session recording, we demonstrate Azure DevOps along with Azure Machine Learning Service to implement build and release pipelines for Machine Learning projects. The content contains source code and pipeline definitions demonstrating how to automate the end-to-end life cycle of custom Machine Learning projects, taking into consideration model deployment as real-time web service. All the techniques and approaches covered in the session are direct from Microsoft commercial engineering and based on real-world solutions with top global enterprise customers.

Use the following link to provision the project we covered during the session on your Azure DevOps organization: https://aka.ms/mlopsreactor

Speaker: Sherif El Mahdi

Sherif is a Senior Industry Software Development Engineer at Microsoft. Sherif is part of Microsoft Commercial Software Engineering and works with Top global enterprise customers with main tech focus on DevOps and AI. https://www.linkedin.com/in/sherifelmahdi

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