Neural Machine Learning I

COMP / ELEC / STAT 502, spring 2020

To register for Sp 2020 instructor permission is required. Please see details under the link Required Background, and email me at

This web site is being updated for implementation of Covid-19 measures in the rest of Sp 2020, changes may occur relative to the posted Syllabus; and relative to previously announced plans. Updates will post in both the Course Schedule below and in Canvas.

Class meets: TR 2:30 - 3:45pm, in Zoom
Instructor: Erzsébet Merényi
Office/Phone: Zoom, 713-348-3595 
Office hour: Tue 4-5pm in Zoom, or by appointment through phone or Zoom
Teaching Assistant: Zhenwei Feng
Advising: TBA

Sample Course Outline
Required Background
Course Flyer
Disability Allowances

Last Updated: April 2, 2020

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. 

2020 Pizza Points are posted on the Canvas home page.

2019 Pizza Points
2018 Project Presentation Scores and Awards

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