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Due to the complexity in putting ML into production, the actual machine learning capability is a small part of a complex system and its lifecycle. This new evolving field is known as MLOps. Informally MLOps typically refers to the collaboration between data scientists and operations engineers (e.g. SRE) to manage the lifecycle of ML within an organization. This space is new and has yet to be explored from a research perspective.
In this workshop we aim to cover research problems in MLOps, including the systems and ML challenges involved in this process. We will also cover the software engineering questions including specification, testing and verification of ML software systems. We will bring together a wide variety of experts from both industry and academia, covering persona ranging from data scientists to machine learning engineers.
For more information please visit the webpage http://mlops-systems.github.io
Author Information
Debo Dutta (Cisco Systems, Inc.)
Matei Zaharia (Stanford and Databricks)
Ce Zhang (ETH)
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