CSci 5521 Fall 2024 - - Notes

Textbook lecture notes - - Lecture notes by Ethem Alpaydin, based on 3rd edition (author of text book, from author's own web site)

There are many entire books on linear algebra. Some of the most readable are by Gilbert Strang (there is an introductory level book and a more advanced one). A short review of the basic theory from a computational/numerical point of view can be found in first part of chapters 2,3,4 of Scientific Computing by Michael Heath, especially chapter 3. See electronic copy of Michael Heath book (available via VPN to the U - you must use 'full tunnel', not 'split tunnel')
Some lectures on linear algebra from MIT.
Some lectures on probability and statistics from MIT.
A brief review of linear algebra.
A Matrix Cookbook.

Topics for the First Test
Discriminant Function: Bayes Analysis with Gaussian Distribution
Bayes Net Example
2D Taylor Expansion, Partial Derivatives and Gradients.
Principal Component using the SVD.
EM.pdf Expectation-Maximization process.
entropy.pdf Information and Entropy (slides) (corrected)
BackPropagation.pdf Simple Back Propagation of Neural Networks
BackPropSoftMax.pdf Back Propagation with a SoftMax function
NNt.pdf Simple Back Propagation of Neural Networks (slides)
SVM-bennet-campbell.pdf Brief Summary of Support Vector Machines
nu-SVM.pdf A geometric interpretation of nu-SVM classifiers

Note: Some of these references are up-to-date, while others may refer to older deprecated constructs.