Most AI Pilots Fail to Scale. MIT Sloan Teaches You Why — and How to Fix It
Build the Finance Skills That Lead to Promotions — Not Just Certificates
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore a thought-provoking presentation on 'Equivariant ML from classical physics' delivered by Soledad Villar from John Hopkins University. Recorded during the weekly DataLearning working group meeting on November 22, 2022, this one-hour talk delves into the intersection of machine learning and classical physics. Gain insights into the development of new technologies based on Data Assimilation and Machine Learning from an interdisciplinary perspective. Discover how equivariant machine learning techniques can be applied to classical physics problems, potentially revolutionizing the field. Engage with cutting-edge research and expand your understanding of this innovative approach to data science and physics.
Syllabus
Data Learning: Equivariant ML from classical physics
Taught by
DataLearning@ICL