MLOps Engineering at Scale

12 Machine learning pipeline

This chapter covers

• Understanding machine learning pipelines with experiment management and hyperparameter optimization
• Implementing Docker containers for the DC taxi model to reduce boilerplate code
• Deploying a machine learning pipeline to train the model

Thus far, you have learned about the individual stages or steps of machine learning in isolation. Focusing on one step of machine learning at a time helped to concentrate your effort on a more manageable scope of work. However, to deploy a production machine learning system it is necessary to integrate these steps into a single pipeline: the outputs of a step flowing into the inputs of the subsequent steps of the pipeline. Further, the pipeline should be flexible ...