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3x09: Focusing MLOps on the Data Scientist with Adam Probst of ZenML
Many data scientists and ML engineers have faced the challenge of putting AI models into production, and this is the core of MLOps. In this episode, Adam Probst, Co-Founder of ZenML, joins Frederic Van Haren and Stephen Foskett to discuss the challenges of putting ML models into production. Machine learning pipelines are inherently complex and fragile and require feedback and tuning, and this requires a new approach with continuous improvement and tight integration. Although reminiscent of DevOps, MLOps demands even more collaboration between IT operations, developers and data scientists, and lines of business. ZenML prepares ready-to-use MLOps infrastructure to these groups so they can focus on the model rather than the platform.
Three Questions
Guests and Hosts
Date: 11/02/2021 Tags: @zenml_io, @SFoskett, @FredericVHaren
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By Tech Field Day
5
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Many data scientists and ML engineers have faced the challenge of putting AI models into production, and this is the core of MLOps. In this episode, Adam Probst, Co-Founder of ZenML, joins Frederic Van Haren and Stephen Foskett to discuss the challenges of putting ML models into production. Machine learning pipelines are inherently complex and fragile and require feedback and tuning, and this requires a new approach with continuous improvement and tight integration. Although reminiscent of DevOps, MLOps demands even more collaboration between IT operations, developers and data scientists, and lines of business. ZenML prepares ready-to-use MLOps infrastructure to these groups so they can focus on the model rather than the platform.
Three Questions
Guests and Hosts
Date: 11/02/2021 Tags: @zenml_io, @SFoskett, @FredericVHaren