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]