Fundamental principles and applications of data-centric research techniques in Physics and Astronomy. Topics include algorithms for data structuring, dimensionality reduction, linear regression and classification, artificial neural nets, convolutional neural nets, unsupervised learning. [1-4-0] Prerequisite: One of MATH 152, MATH 221, MATH 223 and one of MATH 200, MATH 217, MATH 226, MATH 253, MATH 254 and one of BIOL 300, STAT 200, STAT 203, STAT 241, STAT 251, MATH 318 and one of PHYS 210, ...
Fundamental principles and applications of data-centric research techniques in Physics and Astronomy. Topics include algorithms for data structuring, dimensionality reduction, linear regression and classification, artificial neural nets, convolutional neural nets, unsupervised learning. [1-4-0] Prerequisite: One of MATH 152, MATH 221, MATH 223 and one of MATH 200, MATH 217, MATH 226, MATH 253, MATH 254 and one of BIOL 300, STAT 200, STAT 203, STAT 241, STAT 251, MATH 318 and one of PHYS 210, ...
