PUBLICATION: Automated Machine Learning as a Service for the Earth Sciences

Published in AGU Fall Meetings: NASA's JPL team is developing an Automated Machine Learning (AutoML) environment, named MARVIN, to handle large Earth or Space science datasets. MARVIN, part of the DARPA Data Driven Discovery of Models (D3M) program, automates the composition of ML pipelines. It includes a library of ML "primitives" for tasks like preprocessing and feature extraction, and automates the creation of Docker containers for execution on a Kubernetes cluster. The system functions like an "app store" for ML, allowing new capabilities to be added easily. Currently, MARVIN contains over 400 datasets/problems and over 250 primitives.

You can find the publication in it's entirety here: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kXl4GK8AAAAJ&sortby=pubdate&citation_for_view=kXl4GK8AAAAJ:d1gkVwhDpl0C