Scaling Jupyter notebooks with Kubernetes and Tensorflow

One of the most common hurdles with developing AI and deep learning models is to design data pipelines that can operate at scale and in real-time. (...) In this article, you will explore how you can leverage Kubernetes, Tensorflow and Kubeflow to scale your models without having to worry about scaling the infrastructure.

This article actually introduced me an open source project called Kubeflow. From the docs:

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable.

I haven't dug in on this yet but I plan to over the coming week. If you have used Kubeflow before I'd love to hear about your experiences.


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