Computational Physics Seminar
Introduction to Machine Learning
Presented by Dr. Susan Atlas (UNM)
Over the past decade, machine learning ("artificial intelligence") has been transformed from the obscure province of computer science researchers to a ubiquitous and powerful tool in the physical, chemical, and biological sciences. In this talk, I will provide a brief perspective on why and how this change has occurred, introduce the basic concepts of machine learning, and discuss recent sea changes in the field engendered by the rise of neural-network-based deep learning techniques. I will also comment on research aimed at replacing numerical black boxes with interpretable models, driven in part by the ongoing tension between physics- and machine-learned approaches. Examples of applications will be drawn from genomics, structural biology, molecular biophysics, chemical physics, and materials physics. For those who would like to begin exploring machine learning for their own research, I will provide pointers to toolkits and libraries for getting started.
Please contact the host for the password if you would like to attend the seminar through Zoom.
2:00 pm, Friday, November 12, 2021
PAIS-1160, PAIS
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A schedule of talks within the Department of Physics and Astronomy is available on the P&A web site at http://physics.unm.edu/pandaweb/events/index.php