ECE 365: Fundamentals of Machine Learning (Lectures)
You can find the typed notes from the last semester here.
Corresponding Pre-lecture course notes will be given before each lecture. Post-lecture notes will be given after each class session.
Gradescope entry code is N843KK. Please change your gradescope Student ID to your University UIN.
Date | Content | Pre-Lecture | Post-Lecture | Class Recording | |
Lecture 1 | Aug 24th | Introduction to the course; Review of linear algebra and probability | [link] | [link] | [link] |
Lecture 2 | Aug 26th | k-Nearest Neighbor Classifiers and Bayes Classifiers | [link] | [link] | [link] |
Lecture 3 | Aug 31st | Linear Classifiers, Linear Discriminant Analysis, and Logistic Regression | [link] | [link] | [link] |
Lecture 4 | Sep 2nd | Support Vector Machines, Naive Bayes Classifer | [link] | [link] | [link] |
Lecture 5 | Sep 7th | Kernel Trick, How to Handle Data | [link] | [link] | [link] |
Lecture 6 | Sep 9th | K-means Clustering | [link] | [link] | [link] |
Lecture 7 | Sep 14th | Linear Regression | [link] | [link] | [link] |
Lecture 8 | Sep 16th | SVD | [link] | [link] | [link] |
Lecture 9 | Sep 21nd | PCA | [link] | [link] | [link] |
Lecture 10 | Sep 23th | Extra Topics, Wrap up | [link] | [link] | [link] |