Kubeflow Pipelines: From rapid prototyping to production

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135 people went

Google Seattle - Fremont

601 N 34th St · Seattle, WA

How to find us

Enter the building on the 34th Ave entrance.

Location image of event venue


Presenter: Soroush Radpour, Google Cloud AI - Software Engineer

Topic details: Running a machine learning application in production, in a reliable and repeatable manner, is a challenge. This is because an end to end machine learning application entails a lot of phases in addition to model training: data pre-processing and validation, feature engineering, model analysis, deployment, et al. You need a system that makes it easy to compose, orchestrate and run such multi-step pipelines. However, wouldn't it be amazing if the same system also enabled rapid and reliable experimentation of ML techniques for your application. Come learn how Kubeflow enables and simplifies these dual goals.

5:45 - 6:30 PM Networking/Social/Food
6:30 - 6:35 PM Introduction
6:35 - 7:30 PM Talk and Q&A
7:30 - 8:00 PM Networking/Social/Closing