The Data Science Lifecycle provides a process of steps that you can use to structure your data science projects:
The presentation outlines how you can use TensorFlow Extended (TFX) as an end-to-end platform for deploying production machine learning pipelines. A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. Components are built using TFX libraries which can also be used individually.
Resources
TensorFlow Extended Installation Tutorials:
How to use Kubeflow pipelines
TensorFlow Extended resources to learn more about the data science lifecycle steps: