Distributed Machine Learning Patterns

9 A complete implementation

This chapter covers

• Implementing data ingestion component with TensorFlow
• Defining the machine learning model and submitting distributed model training jobs
• Implementing a single-instance model server as well as replicated model servers
• Building an efficient end-to-end workflow of our machine learning system

In the previous chapter of the book, we learned the basics of the four core technologies that we will use in our project: TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. We learned that TensorFlow performs data processing, model building, and model evaluation. We also learned the basic concepts of Kubernetes and started our local Kubernetes cluster, which we will use as our core distributed infrastructure. ...