Subject archive for "model-deployment"

Machine-learning (ML) deployment involves placing a working ML model into an environment where it can do the work it was designed to do. The process of model deployment and monitoring takes a great deal of planning, documentation and oversight, and a variety of different tools.

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer’s "The Ingredients of a Reproducible Machine Learning Model" talk at a recent WiMLDS meetup. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University. Special thanks to Mawer for the permission to excerpt the slides in this Domino Data Science Field Note. The full deck is available here.