Building Cross-Cloud ML Pipelines with Kubeflow with Spark & Tensorflow - Holden Karau

Building Cross-Cloud ML Pipelines with Kubeflow with Spark & Tensorflow - Holden Karau, Google & Trevor Grant, IBM

Data Science, Machine Learning, and Artificial Intelligence has exploded in popularity in the last five years, but the nagging question remains, “How to put models into production?” In this talk, we present KubeFlow- an open source project aims to answer this. This talk will examine how the intricacies involved in taking your pipeline and running it between clouds, mixing data from multiple sources, and building multi-component pipelines. We’ll examine how to tie together multiple tools to prepare your data and train the final model, as well as how to create a serving system to match. The audience will learn how to use kubernetes as a replacement for YARN simplifying your big data stack and empowering your data scientists to self-serve libraries and avoid being responsible for maintaining 20 different incompatible conda environments.

[laura_uzcategui]

One of the best talks I've seen at Kubecon

[dannydk]

So does Kubeflow Pipelines work or not?

[gluteusminimus]

Nice talk, but misleading title. I don't feel there is anything practical about how to make pipelines with Kubeflow/Spark/TensorFlow.