In this post we cover some introductory tutorials on Machine Learning Operations (MLOps), a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.
In particular, we take a look at the following technologies:
- TensorFlow Extended (TFX) is an end-to-end platform for deploying production ML pipelines. When you’re ready to move your models to production, use TFX to create and manage a production pipeline.
- The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Kubeflow pipelines is a component of the Kubeflow project which can be used in combination with TFX.
Overview about how to use Tensor Flow Extended (TFX) with Kubeflow pipelines:
Tensor Flow Extended (TFX)