How to develop a successful ML product? Part III

In the today’s presentation on “end-to-end” ML product development, we discuss on how to put model into production. After a data scientist made their model, there are two aspects to be considered: deployment infrastructure and code quality in model development.

Want to learn more, check the presentation by Magnus Heskestad Waage.