Machine Learning (ML) and Deep Learning (DL) are enabling scientific breakthroughs of unprecedented scale. Ever-increasing volume and variety of geoscientific data suitably positions a wide range of the geosciences to utilize scalable ML and DL methods to complement and, in some instances, to replace traditional approaches. Interest in the application of ML and DL to the geosciences is growing rapidly, as evidenced by substantial increases in the numbers of sessions and attendees at AGU’s ML and DL technical sessions, the 2018 AGU ML workshop, and an increase in ML/DL publications in AGU and other refereed journal articles.

The applications of ML and DL are extremely broad and highly impactful, however, most researchers and practitioners lack a comprehensive background of ML and DL methods and the hands-on experience necessary for effective application and meaningful interpretation of these techniques. Hence there is a large demand for external training, as evidenced by the high attendance of similar tutorials and courses at workshops by industry, universities, research labs, and at other conferences. However, little of these materials are tailored to the specific challenges associated with geoscientific data.

The goal of this tutorial is to teach how to develop ML and DL workflows using open source Python tools, and how to scale those solutions to realistic geoscience datasets on large computational platforms, which is of great relevance to a community where Big-Data is commonplace. This transdisciplinary tutorial will bring together researchers and practitioners across the geosciences, including participants from academia, industry, and the national labs.

Price

$150 (regular)/$75 (student)

If the registration fee is a barrier to your participation in this workshop, Cray Inc. has generously offered to sponsor the registration of some participants. Please contact Karthik Kashinath for more information.