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Ubuntu Blog on Kubeflow Pipelines, MAAS 2.8 and "Masters"

Submitted by Roy Schestowitz on Thursday 25th of June 2020 02:26:32 AM Filed under
Ubuntu
  • Data science workflows on Kubernetes with Kubeflow pipelines: Part 1

    Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is one part of a larger Kubeflow ecosystem that aims to reduce the complexity and time involved with training and deploying machine learning models at scale.

    In this blog series, we demystify Kubeflow pipelines and showcase this method to produce reusable and reproducible data science.

    We go over why Kubeflow brings the right standardization to data science workflows, followed by how this can be achieved through Kubeflow pipelines.

    In part 2, we will get our hands dirty! We’ll make use of the Fashion MNIST dataset and the Basic classification with Tensorflow example, and take a step-by-step approach to turn the example model into a Kubeflow pipeline so that you can do the same.

  • MAAS 2.8 – new features

    This new release of MAAS brings three key new benefits:

    Virtual machines with LXD (Beta)
    Tighter, more responsive UX
    External/remote PostgreSQL database

  • Ubuntu Masters 3: the community expands

    The Ubuntu Masters conference stemmed from a vision to bring the engineering community together to freely exchange innovative ideas, in the spirit of open source. After two hugely successful conferences, connecting IT teams across industries and countries, and featuring speakers from innovators such as Adobe, Netflix, Roblox, and more, Ubuntu Masters returns on June 30th.

»

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