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DevOps for Machine Learning, why is it different?
About This Webinar
DevOps instincts tend to be shaped by what has worked well before. Instincts derived from mainstream software development projects get challenged when we turn to enabling machine learning projects. The key reasons are that the development/delivery workflow is different and the kind of software artefacts involved are different. We will explore the differences and look at emerging open source projects in order to appreciate why the DevOps for machine learning space is growing and the needs that it addresses.
Who can view: People who attended or registered for the webinar only
Webinar Price: Free
Featured Presenters
Ryan Dawson is a core member of the Seldon open source team, providing tooling for machine learning deployments to Kubernetes. He has spent over 10 years working in the Development scene in London across a variety of industries.
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