ECE 365: Fundamentals of Machine Learning (Lectures)
Date | Content | Pre-Lecture | Post-Lecture | |
Lecture 1 | Aug 23th | Introduction to the course; Review of linear algebra and probability | [link] | [link] |
Lecture 2 | Aug 25th | k-Nearest Neighbor Classifiers and Bayes Classifiers | [link] | [link] |
Lecture 3 | Aug 30th | Linear Classifiers and Linear Discriminant Analysis | [link] | [link] |
Lecture 4 | Sep 1st | Naive Bayes Classifer, Kernel Trick | [link] | [link] |
Lecture 5 | Sep 6th | Logistic Regression, SVM, and Model Selection | [link] | [link] |
Lecture 6 | Sep 8th | K-means Clustering and Applications | [link] | [link] |
Lecture 7 | Sep 13th | Linear Regression and Applications | [link] | [link] |
Lecture 8 | Sep 15th | SVD and Eigen-Decomposition | [link] | [link] |
Lecture 9 | Sep 20th | Principal Component Analysis | [link] | [link] |
Lecture 10 | Sep 22nd | Introduction to Neural Networks | [link] | [link] |