In this session, you will learn how to run machine learning workloads with a seamless Azure Machine Learning experience anywhere, including on-premises, in multi-cloud environments, and at the edge. Use any Kubernetes cluster and extend machine learning to run MLOps, model training, real-time inference or batch inference. You can manage all the resources through a single pane with the management, consistency, and reliability.

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Instructor's Bio

Doris Zhong

Product Manager at Microsoft

Doris is focusing on the area of machine learning in hybrid cloud. She loves to communicate with customer to get deep insights, and help solve the real problem. In her early career, she worked on building Microsoft internal GPU training platform, that managed tens of thousands of GPUs, and served thousands of users.


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    UPCOMING Session: Run Azure Machine Learning Anywhere in Multi-cloud or on Premises ​

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