Neural Machine Learning I

COMP / ELEC / STAT 502, spring 2021

This web site may be updated for implementation of Covid-19 measures in the rest of Sp 2021, changes may occur relative to the posted Syllabus and other posting at this site. Updates will post in both the Course Schedule below and in Canvas. 

Class meets: TR 3:10 - 4:30pm, in Zoom (link in Canvas)
Instructor: Erzsébet Merényi
email: erzsebet@rice.edu
Office/Phone: DCH 2082, 713-348-3595  email preferred
Office hour: via Zoom by appointment
Preferred office hour window: Tuesday 6 - 7 pm
Zoom URL sent from Canvas

Grader/TA: Emily Wang
email: eyw3@rice.edu
Advising: Friday 11am - 12pm
Zoom URL in Canvas and in Piazza

Technology TA: Adrianna Garza
email: ajg15@rice.edu Phone: +1(956) 703 7484

Sample Course Outline
Syllabus
Required Background
Course Flyer
Disability Allowances





Last Updated: April 12, 2021
Welcome to biologically inspired neural information processing!
Short course description: Review of major Artificial Neural Network paradigms. Analytical discussion of supervised and unsupervised learning. Emphasis on state-of-the-art Hebbian (biologically most plausible) learning paradigms and their relation to information theoretical methods. Applications to data analysis such as pattern recognition, clustering (information discovery), classification, non-linear PCA, independent component analysis, with lots of examples from image and signal processing and other areas. 

2021 Pizza Points