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]