Towards Modular Machine Learning Pipelines - Microsoft Research
ML pipelinesがもつべき性質
Independently trainable: multiple components can be trained in parallel with very limited communication or coordination needed between them
Consistent: if a component is improved to its optimal version (i.e., replaced with the true data generating process for that component), the pipeline does not degrade
Aligned: if a component is incrementally improved, the pipeline is again guaranteed to not degrade.