Demystifying Kubeflow pipelines: from tensorflow notebook to pipeline

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 webinar, we will demystify Kubeflow Pipelines and demonstrate how you can use this method to produce reusable and reproducible data science. First, we’ll go over why Kubeflow brings the right standardization to data science workflows, followed by how this can be achieved through Kubeflow pipelines. Next, we get our hands dirty! During the demo, we’ll use the Fashion MNIST dataset and the Basic classification with Tensorflow example to take a step-by-step approach to turning this simple example model into a Kubeflow pipeline so that you can do the same. This webinar is part of the joint collaboration between Canonical and Manceps.