AI & BigData Online Day 2020
Enterprise Data Science Workflows on Kubeflow
Central European Time (CET / GMT+1)
December 5th – 13:00 – 13:45
US Eastern Time (EST / GMT-5)
December 5th – 07:00 – 07:45
US Pacific Time (PST / GMT-8)
December 5th – 04:00 – 04:45
How To Attend
In your browser, click the link below
Lesson 1: GitOps and Declarative Infrastructure Revisit the declarative nature of Kubernetes and apply GitOps best practices to get immutable, trackable and reproducible infrastructure. Deploy and manage Kubeflow using the GitOps methodology.
Lesson 2: Reproducible Pipelines with Kale Follow the steps of a data scientist deploying their pipelines in a secure and isolated manner. Try out an end-to-end user workflow right out of your Jupyter Notebook, by leveraging Kale, the easiest way to go from Notebook to Pipeline.
Stefano Fioravanzo is a Software Engineer at Arrikto, his background is in Data Science and ML Research. He understands the value of building robust Machine Learning infrastructure and providing Data Scientist with the necessary tools to scale up their workflows. He works as a full-time contributor to Kubeflow and he is the creator of the Kubeflow Kale project which enables Jupyter Notebooks deployments to Kubeflow Pipelines.
Yannis is a software engineer at Arrikto, working with Kubeflow and the Kubernetes sig-storage group. He loves contributing to open source projects and has authored the Cassandra Operator in Rook and the official Scylla Operator, which he is currently maintaining.