Semester.ly

Johns Hopkins University | EN.520.656

Data Smoothing Using Machine Learning

3.0

credits

Average Course Rating

(4.28)

All measurements contain errors (noise). Before the measurements are used, they should be passed through a noise reduction filter. When the noise level is unknown, the filter can be designed using a machine learning method called cross-validation. This course will investigate algorithmic approaches to data smoothing using cross-validation. Students will complete several Matlab projects.

Spring 2023

Professor: Howard Weinert

(4.28)