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CNCF Webinar Series – From Notebook to Kubeflow Pipelines with MiniKF & Kale
Kubeflow is the de facto standard for running Machine Learning workflows on Kubernetes. Jupyter Notebook is a very popular tool that data scientists use every day to write their ML code, experiment, and visualize the results. However, when it comes to converting a Notebook to a Kubeflow Pipeline, data scientists struggle a lot. It is a very challenging, time-consuming task, and most of the time it needs the cooperation of several different subject-matter experts: Data Scientist, Machine Learning Engineer, Data Engineer.

This webinar will guide you through a seamless workflow that enables data scientists to deploy a Jupyter Notebook as a Kubeflow pipeline with the click of a button. Moreover, we will showcase how a data scientist can reproduce a step of the pipeline run, debug it, and then re-run the pipeline without having to write a single line of code. We will focus on two essential aspects:

-Low barrier to entry: convert a Jupyter Notebook to a multi-step Kubeflow pipeline in the Cloud using only the GUI.
-Reproducibility: automatic data versioning to enable reproducibility and better collaboration between data scientists.

Feb 27, 2020 09:00 AM in Pacific Time (US and Canada)

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Speakers

Vangelis Koukis
CTO & Founder @Arrikto
Vangelis Koukis is the CTO and founder of Arrikto. Vangelis holds a PhD in computer science and has a long history of working in storage, data management, and cloud computing. Arrikto is a core contributor to the Kubeflow project, mainly in the areas of data management and UX. Arrikto creates software to transform how distributed applications discover and consume data on-prem or on the cloud, and empowers end users to iterate faster and easier, creating new collaboration workflows among teams.
Stefano Fioravanzo
Software Engineer @Arrikto
Stefano Fioravanzo is a Software Engineer at Arrikto. Previously he worked as a Research Software Engineer at Fondazione Bruno Kessler, an ICT research center leading AI research in Italy for 40 years. His interests lie in building AI platforms based on Cloud Native technologies, empowering local communities and producers with smart tools. His work involves building a flexible and easy to use environment for Data Scientists that want to scale up their computation in the Cloud.