Subject archive for "model-deployment"

A Guide to Machine Learning 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.
By David Weedmark7 min read

Machine Learning Modeling: How It Works and Why It’s Important
By David Weedmark11 min read


Defining Metrics to Drive Machine Learning Model Adoption & Value
By David Bloch12 min read


Addressing Irreproducibility in the Wild
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.
By Ann Spencer7 min read
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