Description

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. Today we’ll demonstrate how a well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.  We identified design patterns and code that we could leverage. We brought together over 30+ resources from various countries and functions including the Azure ML Product and Engineering team to align the efforts and develop the MLOps v2 accelerator, aligning with the development of Azure Machine Learning v2 platform, CLI, and SDK. The result is we now have a codebase that contains repeatable, automated, and collaborative workflows and patterns that include the best practices for deploying machine learning models to production.


Local ODSC chapter in NYC, USA

Instructor's Bio

Setu Chokshi

Senior Technical Leader, Innovator and Specialist in ML&AI at Microsoft

Setu is also a leader who has gained the respect of his team through active listening and delegating tasks aligned to talents. His background has occurred organically as technical triumphs have led to greater opportunities. He has been fortunate to have worked with industry behemoths—General Electric and Nielsen.

Webinar

  • 1

    ON-DEMAND WEBINAR: Machine Learning Operations (MLOPs) with Azure Machine Learning

    • Ai+ Training

    • Webinar recording

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