Speaker
Prof.
Jeffery Hoch
(UConn Health)
Description
Machine learning is impacting not just the natural sciences but also the social sciences, engineering, architecture, and the art world. In many fields an obstacle to the application of machine learning is the relative paucity of available training data. Other challenges
include the problem of interpreting the results of a machine learning algorithms, incorporating machine learning into hypothesis-driven research, and ethical and reproducible use. This perspective examines the potential of machine learning in NMR structural biology, the role of scientists, and speculates on possible approaches to the hurdles.
Author
Prof.
Jeffery Hoch
(UConn Health)