Dev Ops meets Data Science Taking models from prototype to production with Docker

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PyData DC 2016,We present the evolution of a model to a production API that can scale to large e-commerce needs. On the journey we discuss metrics of success and how to use the Kubernetes cluster manager and associated tools for deploy. In addition to the use of these tools we highlight how to make use of the cluster management system for further testing and experimentation with your models.,The chasm between data science and dev ops is often wide and impenetrable, but the two fields have more in common tha

PyData DC 2016

PyData conferences bring together users and developers of data analysis tools to share ideas and learn from each other. The PyData community gathers to discuss how best to apply Python tools, as we...