Machine learning deserves its own flavor of Continuous Delivery
An ML project ties together large datasets, a slow training process without clear pass/fail acceptance tests, and contains multiple types of deliverables. By comparison, a classical software project just contains code and has a single deliverable (an application). Thankfully, it's possible to create a Machine Learning-specific flavor of Continuous Delivery (CD4ML) for non-enterprise organizations with existing tools today.
Tags: machinelearning, datascience, python, mlops