February 18, 2020

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Lightning Talk: Build a Reproducible ML Workflow with Kubeflow Pipelines

Lightning Talk: Build a Reproducible ML Workflow with Kubeflow Pipelines

Solving a data science problem is an iterative exercise. It requires running experiment after experiment trying new approaches with different parameters and lots of data. To manage this complexity, …
Talk Title Lightning Talk: Build a Reproducible ML Workflow with Kubeflow Pipelines
Speakers Karl Weinmeister (Manager, Developer Advocacy, Google)
Conference Open Source Summit + ELC North America
Conf Tag
Location San Diego, CA, USA
Date Aug 19-23, 2019
URL Talk Page
Slides Talk Slides
Video

Solving a data science problem is an iterative exercise. It requires running experiment after experiment —  trying new approaches with different parameters and lots of data. To manage this complexity, it is very helpful to have a platform to build reusable workflows that can be tracked.Kubeflow Pipelines is a component of the Kubeflow open-source project, focused on building and deploying portable ML workflows on Docker containers. In this session, the audience will learn about KubeFlow Pipelines and how it can help improve reuse and reproducibility of the machine learning process.

container open-source ml complexity data science docker machine learning pipeline
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